{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_data():\n",
    "    df = pd.read_csv(\"comsume.csv\")\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = get_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均现金消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均食品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均衣着消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均居住消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均家庭设备及用品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均医疗保健消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均交通和通信消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均文教娱乐服务消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均其它消费支出(元)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>北京市</td>\n",
       "      <td>19934.5</td>\n",
       "      <td>6392.9</td>\n",
       "      <td>2087.9</td>\n",
       "      <td>1577.4</td>\n",
       "      <td>1377.8</td>\n",
       "      <td>1327.2</td>\n",
       "      <td>3420.9</td>\n",
       "      <td>2901.9</td>\n",
       "      <td>848.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>天津市</td>\n",
       "      <td>16561.8</td>\n",
       "      <td>5940.4</td>\n",
       "      <td>1567.6</td>\n",
       "      <td>1615.6</td>\n",
       "      <td>1119.9</td>\n",
       "      <td>1275.6</td>\n",
       "      <td>2454.4</td>\n",
       "      <td>1899.5</td>\n",
       "      <td>688.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>河北省</td>\n",
       "      <td>10318.3</td>\n",
       "      <td>3335.2</td>\n",
       "      <td>1225.9</td>\n",
       "      <td>1344.5</td>\n",
       "      <td>693.6</td>\n",
       "      <td>923.8</td>\n",
       "      <td>1398.4</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>395.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>山西省</td>\n",
       "      <td>9792.7</td>\n",
       "      <td>3052.6</td>\n",
       "      <td>1205.9</td>\n",
       "      <td>1245.0</td>\n",
       "      <td>612.6</td>\n",
       "      <td>774.9</td>\n",
       "      <td>1340.9</td>\n",
       "      <td>1229.7</td>\n",
       "      <td>331.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>13994.6</td>\n",
       "      <td>4211.5</td>\n",
       "      <td>2203.6</td>\n",
       "      <td>1384.5</td>\n",
       "      <td>948.9</td>\n",
       "      <td>1126.0</td>\n",
       "      <td>1768.7</td>\n",
       "      <td>1641.2</td>\n",
       "      <td>710.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>13280.0</td>\n",
       "      <td>4658.0</td>\n",
       "      <td>1586.8</td>\n",
       "      <td>1314.8</td>\n",
       "      <td>785.7</td>\n",
       "      <td>1079.8</td>\n",
       "      <td>1773.3</td>\n",
       "      <td>1495.9</td>\n",
       "      <td>585.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>11679.0</td>\n",
       "      <td>3767.9</td>\n",
       "      <td>1570.7</td>\n",
       "      <td>1344.4</td>\n",
       "      <td>710.3</td>\n",
       "      <td>1171.3</td>\n",
       "      <td>1363.9</td>\n",
       "      <td>1244.6</td>\n",
       "      <td>506.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>10683.9</td>\n",
       "      <td>3784.7</td>\n",
       "      <td>1608.4</td>\n",
       "      <td>1128.1</td>\n",
       "      <td>618.8</td>\n",
       "      <td>948.4</td>\n",
       "      <td>1191.3</td>\n",
       "      <td>1001.5</td>\n",
       "      <td>402.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>上海市</td>\n",
       "      <td>23200.4</td>\n",
       "      <td>7777.0</td>\n",
       "      <td>1794.1</td>\n",
       "      <td>2166.2</td>\n",
       "      <td>1800.2</td>\n",
       "      <td>1005.5</td>\n",
       "      <td>4076.5</td>\n",
       "      <td>3363.3</td>\n",
       "      <td>1217.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>14357.5</td>\n",
       "      <td>5243.1</td>\n",
       "      <td>1465.5</td>\n",
       "      <td>1234.1</td>\n",
       "      <td>1026.3</td>\n",
       "      <td>805.7</td>\n",
       "      <td>1935.1</td>\n",
       "      <td>2133.3</td>\n",
       "      <td>514.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>17858.2</td>\n",
       "      <td>6118.5</td>\n",
       "      <td>1802.3</td>\n",
       "      <td>1418.0</td>\n",
       "      <td>916.2</td>\n",
       "      <td>1033.7</td>\n",
       "      <td>3437.2</td>\n",
       "      <td>2586.1</td>\n",
       "      <td>546.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>11512.6</td>\n",
       "      <td>4369.6</td>\n",
       "      <td>1225.6</td>\n",
       "      <td>1229.6</td>\n",
       "      <td>678.8</td>\n",
       "      <td>737.1</td>\n",
       "      <td>1356.6</td>\n",
       "      <td>1479.8</td>\n",
       "      <td>435.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>福建省</td>\n",
       "      <td>14750.0</td>\n",
       "      <td>5790.7</td>\n",
       "      <td>1281.3</td>\n",
       "      <td>1606.3</td>\n",
       "      <td>972.2</td>\n",
       "      <td>617.4</td>\n",
       "      <td>2196.9</td>\n",
       "      <td>1786.0</td>\n",
       "      <td>499.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>江西省</td>\n",
       "      <td>10618.7</td>\n",
       "      <td>4195.4</td>\n",
       "      <td>1138.8</td>\n",
       "      <td>1109.8</td>\n",
       "      <td>854.6</td>\n",
       "      <td>524.2</td>\n",
       "      <td>1270.3</td>\n",
       "      <td>1179.9</td>\n",
       "      <td>345.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>山东省</td>\n",
       "      <td>13118.2</td>\n",
       "      <td>4205.9</td>\n",
       "      <td>1745.2</td>\n",
       "      <td>1408.6</td>\n",
       "      <td>915.0</td>\n",
       "      <td>885.8</td>\n",
       "      <td>2140.4</td>\n",
       "      <td>1401.8</td>\n",
       "      <td>415.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>河南省</td>\n",
       "      <td>10838.5</td>\n",
       "      <td>3575.8</td>\n",
       "      <td>1444.6</td>\n",
       "      <td>1080.1</td>\n",
       "      <td>866.7</td>\n",
       "      <td>941.3</td>\n",
       "      <td>1374.8</td>\n",
       "      <td>1137.2</td>\n",
       "      <td>418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>11451.0</td>\n",
       "      <td>4429.3</td>\n",
       "      <td>1415.7</td>\n",
       "      <td>1187.5</td>\n",
       "      <td>867.3</td>\n",
       "      <td>709.6</td>\n",
       "      <td>1205.5</td>\n",
       "      <td>1263.2</td>\n",
       "      <td>372.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>11825.3</td>\n",
       "      <td>4322.1</td>\n",
       "      <td>1277.5</td>\n",
       "      <td>1182.3</td>\n",
       "      <td>903.8</td>\n",
       "      <td>776.9</td>\n",
       "      <td>1541.4</td>\n",
       "      <td>1418.9</td>\n",
       "      <td>402.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>广东省</td>\n",
       "      <td>18489.5</td>\n",
       "      <td>6746.6</td>\n",
       "      <td>1230.7</td>\n",
       "      <td>1925.2</td>\n",
       "      <td>1208.0</td>\n",
       "      <td>929.5</td>\n",
       "      <td>3419.7</td>\n",
       "      <td>2376.0</td>\n",
       "      <td>653.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>11490.1</td>\n",
       "      <td>4372.8</td>\n",
       "      <td>926.4</td>\n",
       "      <td>1166.9</td>\n",
       "      <td>853.6</td>\n",
       "      <td>625.5</td>\n",
       "      <td>1973.0</td>\n",
       "      <td>1243.7</td>\n",
       "      <td>328.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>海南省</td>\n",
       "      <td>10926.7</td>\n",
       "      <td>4896.0</td>\n",
       "      <td>636.1</td>\n",
       "      <td>1103.8</td>\n",
       "      <td>616.3</td>\n",
       "      <td>579.9</td>\n",
       "      <td>1805.1</td>\n",
       "      <td>1004.6</td>\n",
       "      <td>284.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>13335.0</td>\n",
       "      <td>5012.6</td>\n",
       "      <td>1697.6</td>\n",
       "      <td>1276.0</td>\n",
       "      <td>1072.4</td>\n",
       "      <td>1021.5</td>\n",
       "      <td>1384.3</td>\n",
       "      <td>1408.0</td>\n",
       "      <td>462.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>四川省</td>\n",
       "      <td>12105.1</td>\n",
       "      <td>4779.6</td>\n",
       "      <td>1259.5</td>\n",
       "      <td>1126.7</td>\n",
       "      <td>876.3</td>\n",
       "      <td>661.0</td>\n",
       "      <td>1674.1</td>\n",
       "      <td>1224.7</td>\n",
       "      <td>503.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>10058.3</td>\n",
       "      <td>4013.7</td>\n",
       "      <td>1102.4</td>\n",
       "      <td>890.8</td>\n",
       "      <td>673.3</td>\n",
       "      <td>546.8</td>\n",
       "      <td>1270.5</td>\n",
       "      <td>1254.6</td>\n",
       "      <td>306.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>云南省</td>\n",
       "      <td>11074.1</td>\n",
       "      <td>4593.5</td>\n",
       "      <td>1158.8</td>\n",
       "      <td>835.5</td>\n",
       "      <td>509.4</td>\n",
       "      <td>637.9</td>\n",
       "      <td>2039.7</td>\n",
       "      <td>1014.4</td>\n",
       "      <td>285.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>9685.5</td>\n",
       "      <td>4847.6</td>\n",
       "      <td>1158.6</td>\n",
       "      <td>726.6</td>\n",
       "      <td>376.4</td>\n",
       "      <td>385.6</td>\n",
       "      <td>1230.9</td>\n",
       "      <td>478.0</td>\n",
       "      <td>481.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>11821.9</td>\n",
       "      <td>4381.4</td>\n",
       "      <td>1428.2</td>\n",
       "      <td>1126.9</td>\n",
       "      <td>723.7</td>\n",
       "      <td>935.4</td>\n",
       "      <td>1194.8</td>\n",
       "      <td>1595.8</td>\n",
       "      <td>435.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>9895.4</td>\n",
       "      <td>3702.2</td>\n",
       "      <td>1255.7</td>\n",
       "      <td>910.3</td>\n",
       "      <td>597.7</td>\n",
       "      <td>828.6</td>\n",
       "      <td>1076.6</td>\n",
       "      <td>1136.7</td>\n",
       "      <td>387.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>青海省</td>\n",
       "      <td>9613.8</td>\n",
       "      <td>3784.8</td>\n",
       "      <td>1185.6</td>\n",
       "      <td>923.5</td>\n",
       "      <td>644.0</td>\n",
       "      <td>718.8</td>\n",
       "      <td>1116.6</td>\n",
       "      <td>908.1</td>\n",
       "      <td>332.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>11334.4</td>\n",
       "      <td>3768.1</td>\n",
       "      <td>1417.5</td>\n",
       "      <td>1181.7</td>\n",
       "      <td>716.2</td>\n",
       "      <td>890.1</td>\n",
       "      <td>1574.6</td>\n",
       "      <td>1286.2</td>\n",
       "      <td>500.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>10197.1</td>\n",
       "      <td>3694.8</td>\n",
       "      <td>1513.4</td>\n",
       "      <td>898.4</td>\n",
       "      <td>669.9</td>\n",
       "      <td>708.2</td>\n",
       "      <td>1255.9</td>\n",
       "      <td>1012.4</td>\n",
       "      <td>444.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均现金消费支出(元)  城镇居民家庭人均食品消费支出(元)  城镇居民家庭人均衣着消费支出(元)  \\\n",
       "0        北京市            19934.5             6392.9             2087.9   \n",
       "1        天津市            16561.8             5940.4             1567.6   \n",
       "2        河北省            10318.3             3335.2             1225.9   \n",
       "3        山西省             9792.7             3052.6             1205.9   \n",
       "4     内蒙古自治区            13994.6             4211.5             2203.6   \n",
       "5        辽宁省            13280.0             4658.0             1586.8   \n",
       "6        吉林省            11679.0             3767.9             1570.7   \n",
       "7       黑龙江省            10683.9             3784.7             1608.4   \n",
       "8        上海市            23200.4             7777.0             1794.1   \n",
       "9        江苏省            14357.5             5243.1             1465.5   \n",
       "10       浙江省            17858.2             6118.5             1802.3   \n",
       "11       安徽省            11512.6             4369.6             1225.6   \n",
       "12       福建省            14750.0             5790.7             1281.3   \n",
       "13       江西省            10618.7             4195.4             1138.8   \n",
       "14       山东省            13118.2             4205.9             1745.2   \n",
       "15       河南省            10838.5             3575.8             1444.6   \n",
       "16       湖北省            11451.0             4429.3             1415.7   \n",
       "17       湖南省            11825.3             4322.1             1277.5   \n",
       "18       广东省            18489.5             6746.6             1230.7   \n",
       "19   广西壮族自治区            11490.1             4372.8              926.4   \n",
       "20       海南省            10926.7             4896.0              636.1   \n",
       "21       重庆市            13335.0             5012.6             1697.6   \n",
       "22       四川省            12105.1             4779.6             1259.5   \n",
       "23       贵州省            10058.3             4013.7             1102.4   \n",
       "24       云南省            11074.1             4593.5             1158.8   \n",
       "25     西藏自治区             9685.5             4847.6             1158.6   \n",
       "26       陕西省            11821.9             4381.4             1428.2   \n",
       "27       甘肃省             9895.4             3702.2             1255.7   \n",
       "28       青海省             9613.8             3784.8             1185.6   \n",
       "29   宁夏回族自治区            11334.4             3768.1             1417.5   \n",
       "30  新疆维吾尔自治区            10197.1             3694.8             1513.4   \n",
       "\n",
       "    城镇居民家庭人均居住消费支出(元)  城镇居民家庭人均家庭设备及用品消费支出(元)  城镇居民家庭人均医疗保健消费支出(元)  \\\n",
       "0              1577.4                  1377.8               1327.2   \n",
       "1              1615.6                  1119.9               1275.6   \n",
       "2              1344.5                   693.6                923.8   \n",
       "3              1245.0                   612.6                774.9   \n",
       "4              1384.5                   948.9               1126.0   \n",
       "5              1314.8                   785.7               1079.8   \n",
       "6              1344.4                   710.3               1171.3   \n",
       "7              1128.1                   618.8                948.4   \n",
       "8              2166.2                  1800.2               1005.5   \n",
       "9              1234.1                  1026.3                805.7   \n",
       "10             1418.0                   916.2               1033.7   \n",
       "11             1229.6                   678.8                737.1   \n",
       "12             1606.3                   972.2                617.4   \n",
       "13             1109.8                   854.6                524.2   \n",
       "14             1408.6                   915.0                885.8   \n",
       "15             1080.1                   866.7                941.3   \n",
       "16             1187.5                   867.3                709.6   \n",
       "17             1182.3                   903.8                776.9   \n",
       "18             1925.2                  1208.0                929.5   \n",
       "19             1166.9                   853.6                625.5   \n",
       "20             1103.8                   616.3                579.9   \n",
       "21             1276.0                  1072.4               1021.5   \n",
       "22             1126.7                   876.3                661.0   \n",
       "23              890.8                   673.3                546.8   \n",
       "24              835.5                   509.4                637.9   \n",
       "25              726.6                   376.4                385.6   \n",
       "26             1126.9                   723.7                935.4   \n",
       "27              910.3                   597.7                828.6   \n",
       "28              923.5                   644.0                718.8   \n",
       "29             1181.7                   716.2                890.1   \n",
       "30              898.4                   669.9                708.2   \n",
       "\n",
       "    城镇居民家庭人均交通和通信消费支出(元)  城镇居民家庭人均文教娱乐服务消费支出(元)  城镇居民家庭人均其它消费支出(元)  \n",
       "0                 3420.9                 2901.9              848.5  \n",
       "1                 2454.4                 1899.5              688.7  \n",
       "2                 1398.4                 1001.0              395.9  \n",
       "3                 1340.9                 1229.7              331.1  \n",
       "4                 1768.7                 1641.2              710.4  \n",
       "5                 1773.3                 1495.9              585.8  \n",
       "6                 1363.9                 1244.6              506.1  \n",
       "7                 1191.3                 1001.5              402.7  \n",
       "8                 4076.5                 3363.3             1217.7  \n",
       "9                 1935.1                 2133.3              514.4  \n",
       "10                3437.2                 2586.1              546.4  \n",
       "11                1356.6                 1479.8              435.6  \n",
       "12                2196.9                 1786.0              499.3  \n",
       "13                1270.3                 1179.9              345.7  \n",
       "14                2140.4                 1401.8              415.6  \n",
       "15                1374.8                 1137.2              418.0  \n",
       "16                1205.5                 1263.2              372.9  \n",
       "17                1541.4                 1418.9              402.5  \n",
       "18                3419.7                 2376.0              653.8  \n",
       "19                1973.0                 1243.7              328.3  \n",
       "20                1805.1                 1004.6              284.9  \n",
       "21                1384.3                 1408.0              462.8  \n",
       "22                1674.1                 1224.7              503.1  \n",
       "23                1270.5                 1254.6              306.2  \n",
       "24                2039.7                 1014.4              285.0  \n",
       "25                1230.9                  478.0              481.8  \n",
       "26                1194.8                 1595.8              435.7  \n",
       "27                1076.6                 1136.7              387.5  \n",
       "28                1116.6                  908.1              332.5  \n",
       "29                1574.6                 1286.2              500.1  \n",
       "30                1255.9                 1012.4              444.2  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 31 entries, 0 to 30\n",
      "Data columns (total 10 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   地区                      31 non-null     object \n",
      " 1   城镇居民家庭人均现金消费支出(元)       31 non-null     float64\n",
      " 2   城镇居民家庭人均食品消费支出(元)       31 non-null     float64\n",
      " 3   城镇居民家庭人均衣着消费支出(元)       31 non-null     float64\n",
      " 4   城镇居民家庭人均居住消费支出(元)       31 non-null     float64\n",
      " 5   城镇居民家庭人均家庭设备及用品消费支出(元)  31 non-null     float64\n",
      " 6   城镇居民家庭人均医疗保健消费支出(元)     31 non-null     float64\n",
      " 7   城镇居民家庭人均交通和通信消费支出(元)    31 non-null     float64\n",
      " 8   城镇居民家庭人均文教娱乐服务消费支出(元)   31 non-null     float64\n",
      " 9   城镇居民家庭人均其它消费支出(元)       31 non-null     float64\n",
      "dtypes: float64(9), object(1)\n",
      "memory usage: 2.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>城镇居民家庭人均现金消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均食品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均衣着消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均居住消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均家庭设备及用品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均医疗保健消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均交通和通信消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均文教娱乐服务消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均其它消费支出(元)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>12767.809677</td>\n",
       "      <td>4637.558065</td>\n",
       "      <td>1407.029032</td>\n",
       "      <td>1247.390323</td>\n",
       "      <td>845.351613</td>\n",
       "      <td>843.000000</td>\n",
       "      <td>1814.912903</td>\n",
       "      <td>1487.354839</td>\n",
       "      <td>485.264516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3305.346861</td>\n",
       "      <td>1074.174300</td>\n",
       "      <td>322.601350</td>\n",
       "      <td>306.233298</td>\n",
       "      <td>276.020225</td>\n",
       "      <td>225.236976</td>\n",
       "      <td>783.647991</td>\n",
       "      <td>619.007245</td>\n",
       "      <td>188.734131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>9613.800000</td>\n",
       "      <td>3052.600000</td>\n",
       "      <td>636.100000</td>\n",
       "      <td>726.600000</td>\n",
       "      <td>376.400000</td>\n",
       "      <td>385.600000</td>\n",
       "      <td>1076.600000</td>\n",
       "      <td>478.000000</td>\n",
       "      <td>284.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10651.300000</td>\n",
       "      <td>3784.750000</td>\n",
       "      <td>1215.750000</td>\n",
       "      <td>1106.800000</td>\n",
       "      <td>671.600000</td>\n",
       "      <td>684.600000</td>\n",
       "      <td>1270.400000</td>\n",
       "      <td>1136.950000</td>\n",
       "      <td>380.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>11512.600000</td>\n",
       "      <td>4372.800000</td>\n",
       "      <td>1415.700000</td>\n",
       "      <td>1187.500000</td>\n",
       "      <td>853.600000</td>\n",
       "      <td>828.600000</td>\n",
       "      <td>1541.400000</td>\n",
       "      <td>1263.200000</td>\n",
       "      <td>435.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>13664.800000</td>\n",
       "      <td>4954.300000</td>\n",
       "      <td>1578.750000</td>\n",
       "      <td>1364.500000</td>\n",
       "      <td>932.550000</td>\n",
       "      <td>976.950000</td>\n",
       "      <td>2006.350000</td>\n",
       "      <td>1618.500000</td>\n",
       "      <td>510.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>23200.400000</td>\n",
       "      <td>7777.000000</td>\n",
       "      <td>2203.600000</td>\n",
       "      <td>2166.200000</td>\n",
       "      <td>1800.200000</td>\n",
       "      <td>1327.200000</td>\n",
       "      <td>4076.500000</td>\n",
       "      <td>3363.300000</td>\n",
       "      <td>1217.700000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       城镇居民家庭人均现金消费支出(元)  城镇居民家庭人均食品消费支出(元)  城镇居民家庭人均衣着消费支出(元)  \\\n",
       "count          31.000000          31.000000          31.000000   \n",
       "mean        12767.809677        4637.558065        1407.029032   \n",
       "std          3305.346861        1074.174300         322.601350   \n",
       "min          9613.800000        3052.600000         636.100000   \n",
       "25%         10651.300000        3784.750000        1215.750000   \n",
       "50%         11512.600000        4372.800000        1415.700000   \n",
       "75%         13664.800000        4954.300000        1578.750000   \n",
       "max         23200.400000        7777.000000        2203.600000   \n",
       "\n",
       "       城镇居民家庭人均居住消费支出(元)  城镇居民家庭人均家庭设备及用品消费支出(元)  城镇居民家庭人均医疗保健消费支出(元)  \\\n",
       "count          31.000000               31.000000            31.000000   \n",
       "mean         1247.390323              845.351613           843.000000   \n",
       "std           306.233298              276.020225           225.236976   \n",
       "min           726.600000              376.400000           385.600000   \n",
       "25%          1106.800000              671.600000           684.600000   \n",
       "50%          1187.500000              853.600000           828.600000   \n",
       "75%          1364.500000              932.550000           976.950000   \n",
       "max          2166.200000             1800.200000          1327.200000   \n",
       "\n",
       "       城镇居民家庭人均交通和通信消费支出(元)  城镇居民家庭人均文教娱乐服务消费支出(元)  城镇居民家庭人均其它消费支出(元)  \n",
       "count             31.000000              31.000000          31.000000  \n",
       "mean            1814.912903            1487.354839         485.264516  \n",
       "std              783.647991             619.007245         188.734131  \n",
       "min             1076.600000             478.000000         284.900000  \n",
       "25%             1270.400000            1136.950000         380.200000  \n",
       "50%             1541.400000            1263.200000         435.700000  \n",
       "75%             2006.350000            1618.500000         510.250000  \n",
       "max             4076.500000            3363.300000        1217.700000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据分析\n",
    "# 城镇居民家庭人均现金消费"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='城镇居民家庭人均现金消费支出(元)'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号\n",
    "sns.distplot(df['城镇居民家庭人均现金消费支出(元)'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**城镇居民家庭人均现金消费大部分在一万到一万五之间**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.barh(df['地区'],width=df['城镇居民家庭人均现金消费支出(元)'])\n",
    "plt.grid()\n",
    "plt.title(\"各省市城镇居民家庭人均现金消费支出\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均现金消费支出(元)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>上海市</td>\n",
       "      <td>23200.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>北京市</td>\n",
       "      <td>19934.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>广东省</td>\n",
       "      <td>18489.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>17858.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>天津市</td>\n",
       "      <td>16561.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>福建省</td>\n",
       "      <td>14750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>14357.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>13994.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>13335.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>13280.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>山东省</td>\n",
       "      <td>13118.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>四川省</td>\n",
       "      <td>12105.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>11825.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>11821.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>11679.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>11512.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>11490.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>11451.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>11334.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>云南省</td>\n",
       "      <td>11074.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>海南省</td>\n",
       "      <td>10926.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>河南省</td>\n",
       "      <td>10838.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>10683.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>江西省</td>\n",
       "      <td>10618.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>河北省</td>\n",
       "      <td>10318.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>10197.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>10058.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>9895.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>山西省</td>\n",
       "      <td>9792.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>9685.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>青海省</td>\n",
       "      <td>9613.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均现金消费支出(元)\n",
       "排名                             \n",
       "1        上海市            23200.4\n",
       "2        北京市            19934.5\n",
       "3        广东省            18489.5\n",
       "4        浙江省            17858.2\n",
       "5        天津市            16561.8\n",
       "6        福建省            14750.0\n",
       "7        江苏省            14357.5\n",
       "8     内蒙古自治区            13994.6\n",
       "9        重庆市            13335.0\n",
       "10       辽宁省            13280.0\n",
       "11       山东省            13118.2\n",
       "12       四川省            12105.1\n",
       "13       湖南省            11825.3\n",
       "14       陕西省            11821.9\n",
       "15       吉林省            11679.0\n",
       "16       安徽省            11512.6\n",
       "17   广西壮族自治区            11490.1\n",
       "18       湖北省            11451.0\n",
       "19   宁夏回族自治区            11334.4\n",
       "20       云南省            11074.1\n",
       "21       海南省            10926.7\n",
       "22       河南省            10838.5\n",
       "23      黑龙江省            10683.9\n",
       "24       江西省            10618.7\n",
       "25       河北省            10318.3\n",
       "26  新疆维吾尔自治区            10197.1\n",
       "27       贵州省            10058.3\n",
       "28       甘肃省             9895.4\n",
       "29       山西省             9792.7\n",
       "30     西藏自治区             9685.5\n",
       "31       青海省             9613.8"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cash = df[['地区', '城镇居民家庭人均现金消费支出(元)']].sort_values(by='城镇居民家庭人均现金消费支出(元)', ascending=False)\n",
    "rank = pd.Index(name='排名', data=range(1,32))\n",
    "cash.index = rank\n",
    "cash"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**1.上海城镇居民人均现金消费支出最多遥遥领先23200.4元是唯一一个超过两万元的，北京排第二19934.5元，第三是广东18489.5元。**\n",
    "\n",
    "**2.前十的省份中只有内蒙和重庆市内陆省份，以13994.6元和13335.0元分裂8、9名**\n",
    "\n",
    "**3.最少的是西部地区，青海9613.8元、西藏9685.5元分列倒数第一和倒数第二。抛开遥遥领先的上海，是北京广东的一半左右**\n",
    "\n",
    "**4. 前八的省市的人均现金消费支出位于全国各省市人均现金消费支出的75%分位数以上**\n",
    "\n",
    "**5.河北省、新疆维吾尔自治区、贵州省、甘肃、山西、西藏、青海位于25%分位数以下**\n",
    "\n",
    "**6. 前19个省份超过了人均现金消费支出的中位数**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plt_dist(col):\n",
    "    \"\"\"\n",
    "    绘制某一列特征的分布情况\n",
    "    \"\"\"\n",
    "    sns.distplot(df[col])\n",
    "    plt.title(col)\n",
    "    plt.show()\n",
    "    \n",
    "def plt_region_dist(col):\n",
    "    \"\"\"\n",
    "    绘制某一特征的地区分布\n",
    "    \"\"\"\n",
    "    plt.figure(figsize=(10,10))\n",
    "    plt.barh(df['地区'],width=df[col])\n",
    "    plt.grid()\n",
    "    plt.title(col)\n",
    "    plt.show()\n",
    "    \n",
    "def get_rank(col):\n",
    "    \"\"\"\n",
    "    获取某以特征的排名\n",
    "    \"\"\"\n",
    "    data = df[['地区', col]].sort_values(by=col, ascending=False)\n",
    "    rank = pd.Index(name='排名', data=range(1,32))\n",
    "    data.index = rank\n",
    "    return data\n",
    "\n",
    "def get_per(col, name):\n",
    "    \"\"\"\n",
    "    获取某种支出的占总现金消费支出的比例\n",
    "    \"\"\"\n",
    "    df[name] = df[col]/ df['城镇居民家庭人均现金消费支出(元)']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 城镇居民家庭人均食品消费支出(元)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_dist('城镇居民家庭人均食品消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_region_dist('城镇居民家庭人均食品消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均食品消费支出(元)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>上海市</td>\n",
       "      <td>7777.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>广东省</td>\n",
       "      <td>6746.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>北京市</td>\n",
       "      <td>6392.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>6118.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>天津市</td>\n",
       "      <td>5940.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>福建省</td>\n",
       "      <td>5790.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>5243.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>5012.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>海南省</td>\n",
       "      <td>4896.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>4847.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>四川省</td>\n",
       "      <td>4779.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>4658.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>云南省</td>\n",
       "      <td>4593.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>4429.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>4381.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>4372.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>4369.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>4322.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>4211.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>山东省</td>\n",
       "      <td>4205.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>江西省</td>\n",
       "      <td>4195.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>4013.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>青海省</td>\n",
       "      <td>3784.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>3784.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>3768.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>3767.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>3702.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>3694.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>河南省</td>\n",
       "      <td>3575.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>河北省</td>\n",
       "      <td>3335.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>山西省</td>\n",
       "      <td>3052.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均食品消费支出(元)\n",
       "排名                             \n",
       "1        上海市             7777.0\n",
       "2        广东省             6746.6\n",
       "3        北京市             6392.9\n",
       "4        浙江省             6118.5\n",
       "5        天津市             5940.4\n",
       "6        福建省             5790.7\n",
       "7        江苏省             5243.1\n",
       "8        重庆市             5012.6\n",
       "9        海南省             4896.0\n",
       "10     西藏自治区             4847.6\n",
       "11       四川省             4779.6\n",
       "12       辽宁省             4658.0\n",
       "13       云南省             4593.5\n",
       "14       湖北省             4429.3\n",
       "15       陕西省             4381.4\n",
       "16   广西壮族自治区             4372.8\n",
       "17       安徽省             4369.6\n",
       "18       湖南省             4322.1\n",
       "19    内蒙古自治区             4211.5\n",
       "20       山东省             4205.9\n",
       "21       江西省             4195.4\n",
       "22       贵州省             4013.7\n",
       "23       青海省             3784.8\n",
       "24      黑龙江省             3784.7\n",
       "25   宁夏回族自治区             3768.1\n",
       "26       吉林省             3767.9\n",
       "27       甘肃省             3702.2\n",
       "28  新疆维吾尔自治区             3694.8\n",
       "29       河南省             3575.8\n",
       "30       河北省             3335.2\n",
       "31       山西省             3052.6"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_rank('城镇居民家庭人均食品消费支出(元)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. 人均食品消费支出前7名没什么变化，依然是北上广天津福建江苏\n",
    "2. 西藏从人均现金支出的倒数第二名上升到了第10名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "get_per('城镇居民家庭人均食品消费支出(元)', 'engle') # 食品消费占总消费的支出比，恩格尔系数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>engle</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>0.500501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>海南省</td>\n",
       "      <td>0.448077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>云南省</td>\n",
       "      <td>0.414797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>0.399044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>江西省</td>\n",
       "      <td>0.395095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>四川省</td>\n",
       "      <td>0.394842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>青海省</td>\n",
       "      <td>0.393684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>福建省</td>\n",
       "      <td>0.392590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>0.386805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>0.380571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>0.379549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>0.375898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>0.374133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>0.370617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>0.365496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>0.365182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>广东省</td>\n",
       "      <td>0.364888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>0.362338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>天津市</td>\n",
       "      <td>0.358681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>0.354243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>0.350753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>0.342616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>上海市</td>\n",
       "      <td>0.335210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>0.332448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>河南省</td>\n",
       "      <td>0.329917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>河北省</td>\n",
       "      <td>0.323232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>0.322622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>北京市</td>\n",
       "      <td>0.320695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>山东省</td>\n",
       "      <td>0.320616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>山西省</td>\n",
       "      <td>0.311722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>0.300938</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区     engle\n",
       "排名                    \n",
       "1      西藏自治区  0.500501\n",
       "2        海南省  0.448077\n",
       "3        云南省  0.414797\n",
       "4        贵州省  0.399044\n",
       "5        江西省  0.395095\n",
       "6        四川省  0.394842\n",
       "7        青海省  0.393684\n",
       "8        福建省  0.392590\n",
       "9        湖北省  0.386805\n",
       "10   广西壮族自治区  0.380571\n",
       "11       安徽省  0.379549\n",
       "12       重庆市  0.375898\n",
       "13       甘肃省  0.374133\n",
       "14       陕西省  0.370617\n",
       "15       湖南省  0.365496\n",
       "16       江苏省  0.365182\n",
       "17       广东省  0.364888\n",
       "18  新疆维吾尔自治区  0.362338\n",
       "19       天津市  0.358681\n",
       "20      黑龙江省  0.354243\n",
       "21       辽宁省  0.350753\n",
       "22       浙江省  0.342616\n",
       "23       上海市  0.335210\n",
       "24   宁夏回族自治区  0.332448\n",
       "25       河南省  0.329917\n",
       "26       河北省  0.323232\n",
       "27       吉林省  0.322622\n",
       "28       北京市  0.320695\n",
       "29       山东省  0.320616\n",
       "30       山西省  0.311722\n",
       "31    内蒙古自治区  0.300938"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_rank('engle')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1.  西藏自治区  0.500501\n",
    "2.\t海南省\t    0.448077\n",
    "3.\t云南省\t    0.414797\n",
    "4.\t贵州省\t    0.399044\n",
    "5.\t江西省\t    0.395095\n",
    "6.\t四川省\t    0.394842\n",
    "7.\t青海省\t    0.393684\n",
    "\n",
    "西藏的恩格尔系数果然是最高的，达到0.5，海南和云南也超过了0.4，贵州、江西、四川、青海也十分接近0.4\n",
    "\n",
    "福建有点让人意外，也到达了0.39"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 城镇居民家庭人均衣着消费支出(元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_dist('城镇居民家庭人均衣着消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_region_dist('城镇居民家庭人均衣着消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均衣着消费支出(元)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>2203.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>北京市</td>\n",
       "      <td>2087.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>1802.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>上海市</td>\n",
       "      <td>1794.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>山东省</td>\n",
       "      <td>1745.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>1697.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>1608.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>1586.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>1570.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>天津市</td>\n",
       "      <td>1567.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>1513.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>1465.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>河南省</td>\n",
       "      <td>1444.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>1428.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>1417.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>1415.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>福建省</td>\n",
       "      <td>1281.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>1277.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>四川省</td>\n",
       "      <td>1259.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>1255.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>广东省</td>\n",
       "      <td>1230.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>河北省</td>\n",
       "      <td>1225.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>1225.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>山西省</td>\n",
       "      <td>1205.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>青海省</td>\n",
       "      <td>1185.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>云南省</td>\n",
       "      <td>1158.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>1158.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>江西省</td>\n",
       "      <td>1138.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>1102.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>926.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>海南省</td>\n",
       "      <td>636.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均衣着消费支出(元)\n",
       "排名                             \n",
       "1     内蒙古自治区             2203.6\n",
       "2        北京市             2087.9\n",
       "3        浙江省             1802.3\n",
       "4        上海市             1794.1\n",
       "5        山东省             1745.2\n",
       "6        重庆市             1697.6\n",
       "7       黑龙江省             1608.4\n",
       "8        辽宁省             1586.8\n",
       "9        吉林省             1570.7\n",
       "10       天津市             1567.6\n",
       "11  新疆维吾尔自治区             1513.4\n",
       "12       江苏省             1465.5\n",
       "13       河南省             1444.6\n",
       "14       陕西省             1428.2\n",
       "15   宁夏回族自治区             1417.5\n",
       "16       湖北省             1415.7\n",
       "17       福建省             1281.3\n",
       "18       湖南省             1277.5\n",
       "19       四川省             1259.5\n",
       "20       甘肃省             1255.7\n",
       "21       广东省             1230.7\n",
       "22       河北省             1225.9\n",
       "23       安徽省             1225.6\n",
       "24       山西省             1205.9\n",
       "25       青海省             1185.6\n",
       "26       云南省             1158.8\n",
       "27     西藏自治区             1158.6\n",
       "28       江西省             1138.8\n",
       "29       贵州省             1102.4\n",
       "30   广西壮族自治区              926.4\n",
       "31       海南省              636.1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_rank('城镇居民家庭人均衣着消费支出(元)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**内蒙竟然是衣着消费支出最多的，出收入水平外可能与地域有一定关系，东北三省也排在前10名，冬天天气寒冷需要购买冬装，冬装一般是比较贵的。热带地区的海南衣着消费是最低，而且是倒数第二的广西70%,是倒数第三的贵州的57%**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "get_per('城镇居民家庭人均衣着消费支出(元)', 'cloth_per')  # 衣物支出占比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>cloth_per</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>0.157461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>0.150544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>0.148415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>0.134489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>河南省</td>\n",
       "      <td>0.133284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>山东省</td>\n",
       "      <td>0.133037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>0.127304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>0.126897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>0.125062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>0.123631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>青海省</td>\n",
       "      <td>0.123323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>山西省</td>\n",
       "      <td>0.123143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>0.120810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>0.119622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>0.119488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>河北省</td>\n",
       "      <td>0.118808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>0.109601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>0.108031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>江西省</td>\n",
       "      <td>0.107245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>0.106457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>北京市</td>\n",
       "      <td>0.104738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>云南省</td>\n",
       "      <td>0.104641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>四川省</td>\n",
       "      <td>0.104047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>0.102072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>0.100923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>天津市</td>\n",
       "      <td>0.094652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>福建省</td>\n",
       "      <td>0.086868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>0.080626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>上海市</td>\n",
       "      <td>0.077331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>广东省</td>\n",
       "      <td>0.066562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>海南省</td>\n",
       "      <td>0.058215</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  cloth_per\n",
       "排名                     \n",
       "1     内蒙古自治区   0.157461\n",
       "2       黑龙江省   0.150544\n",
       "3   新疆维吾尔自治区   0.148415\n",
       "4        吉林省   0.134489\n",
       "5        河南省   0.133284\n",
       "6        山东省   0.133037\n",
       "7        重庆市   0.127304\n",
       "8        甘肃省   0.126897\n",
       "9    宁夏回族自治区   0.125062\n",
       "10       湖北省   0.123631\n",
       "11       青海省   0.123323\n",
       "12       山西省   0.123143\n",
       "13       陕西省   0.120810\n",
       "14     西藏自治区   0.119622\n",
       "15       辽宁省   0.119488\n",
       "16       河北省   0.118808\n",
       "17       贵州省   0.109601\n",
       "18       湖南省   0.108031\n",
       "19       江西省   0.107245\n",
       "20       安徽省   0.106457\n",
       "21       北京市   0.104738\n",
       "22       云南省   0.104641\n",
       "23       四川省   0.104047\n",
       "24       江苏省   0.102072\n",
       "25       浙江省   0.100923\n",
       "26       天津市   0.094652\n",
       "27       福建省   0.086868\n",
       "28   广西壮族自治区   0.080626\n",
       "29       上海市   0.077331\n",
       "30       广东省   0.066562\n",
       "31       海南省   0.058215"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_rank('cloth_per')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**海南的衣着支出之占总现金消费支出的5.8%， 而内蒙占比15.77%**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 城镇居民家庭人均现金消费支出(元)\t\n",
    "# 城镇居民家庭人均食品消费支出(元)\t\n",
    "# 城镇居民家庭人均衣着消费支出(元)\t\n",
    "# 城镇居民家庭人均居住消费支出(元)\t\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 城镇居民家庭人均居住消费支出(元)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MLRYcjDHG1GLBwRhjTC0WHIwxxtRiwcEYY0wtFhyMMcbUYsHBGGNMLRYcjDHG1GLBwRhjTC0WHIwxxtRiwcEYY0wtFhyMMcbUYsHBGGNMLb6Cg4g8KiKzRWRyQ/LUkdZBRGYGfb5bRGZ4r+UicoeIdBKRzUHpOUe6g8YYYxqu3uAgIpcCsao6CsgTkT5+8tSRlg08AaQGllXVuwLPlAYWA08CJwO/CXrWdH4j7Ksxxhif/LQcxnHwWc4fAqN95gmXVg1cCRSGrkBETgS2qOoWYCRws4h8KiJ/DVcoEZkkIvNEZF5+vsUOY4xpTH6CQyqwxXtfCHTwmadWmqoWqmpBHdu5Bbjfe/82MEpVTwH6isiQ0MyqOkVVR6jqiJwc63UyxpjG5Cc4FAPJ3vu0OpYJl8fPcgCISBbQXlXXeEmzVbXIe78cqNWVZYwx5tjxExzmc7AraSiw3mceP8sFXAS8FfR5mojkikgKMAFY4qOcxhhjGkmcjzxTgZkikgdMBK4SkXtVdfJh8owENExaXSYA9wV9vhuYDlQAD6vqCn+7Y4wxpjHUGxxUtVBExgFnAX9U1e3AwnryFACES/PyjwtZ/uqQz9OBfg3cF2OMMY3ET8sBVd3LwSuPfOfxs5wxR6OwtJIFm/axeV8pu4vL6Z+bwXmDc8lMiY900YyJanaHtIla+UXlPPTRGt5Zup0te/eTGBfDh8t3cuofPuTJT9dHunjGRDVfLQdjmpttBaU89sl6AL4/vjd5We7CuO0FZSzcvI9fvraUpPhYrhjRJYKlNCZ6WcvBRJ395VU8NmsdcTHCpDE9DwQGgI6ZSTzyzRGM6dOOO15ZzIfLd0SwpMZELwsOJuq899UOSiur+cYp3chJT6z1fXxsDA9dO5wBuRl87+kvWberJAKlNCa6WXAwUWVbQSlz1+3h5B5tyc1MrjNfWmIc//7GCGJjhLteX4qqNmEpjYl+FhxM1FBV3li4leSEWM7sH24Wl0N1zEziJ2f35eOV+by9ZHsTlNCYlsOCg4kay7YVsn73fiYM6EhyQqyvZa4b2Y0BuRnc88YyisurjnEJjWk5LDiYqDF7zW6yUuIZ3j3b9zJxsTHce8kgtheW8fCMNfUvYIwBLDiYKLGjsIx1u0o4uUdbYkQatOywrtmcNziXJ2avp6C08hiV0JiWxYKDiQpz1u4mLkYY0c1/qyHY98b3pqi8iidnr2/cghnTQllwMM1eWWU1X27ax+BOmaQmHtl9mwPyMjijX3se/WQdJTb2YEy9LDiYZm/Bpn1UVNUwsmfbo1rP907vzb79lTzz2cZGKpkxLZcFB9PszVu/h7ysJDpn131fgx/DumYzunc7/j1zLRVVNY1UOmNaJgsOplnbXVzO1oIyju+chTRwIDqcb4/pwc6ict5dZvc9GHM4FhxMs7Z4i3sMyKBOmY2yvrF9cujSJpknP93QKOszpqWy4GCatSVbCuiSnUxWSkKjrC8mRrj25G7MXbeHFduL6l/AmFbKV3AQkUdFZLaITG5InjrSOojIzKDPnURks4jM8F45frdpWrZAl9LgRmo1BFwxogsJcTE8NWd9o67XmJak3uAgIpcCsao6CsgTkT5+8tSRlg08AaQGLX4y8BtVHee98v1s07R8jd2lFJCdmsAFQ/J49YstFJXZTXHGhOOn5TCOg4/6/BAY7TNPuLRq4EqgMGjZkcDNIvKpiPy1Ads0LVxjdykFu+6UbpRUVPP6wq2Nvm5jWgI/wSEV2OK9LwTCTYcZLk+tNFUtVNWCkGXfBkap6ilAXxEZ4mebIjJJROaJyLz8/Hwfu2GiyZ6SCrYWlDV6qyFgaOdMjuuQzkvzNx+T9RsT7fwEh2IgcIF5Wh3LhMvjZzmA2aoaGBlcDvTxs6yqTlHVEao6Iicnx8dumGiyYrtrXA7IzTgm6xcRLhvemS837mP1ThuYNiaUn+Awn4PdOkOB9T7z+FkOYJqI5IpICjABWNKAZU0LtWJHEW1TE2ibVvtJb43lohPyiI0RXpq/pf7MxrQyfiaqmQrMFJE8YCJwlYjcq6qTD5NnJKBh0sK5G5gOVAAPq+oKEdnmc1nTAlVW17A2v4QTe7Q5pttpn57E+ONyeOWLzdx6dl/iYu3KbmMC6v1vUNVC3ADxHGC8qi4MCQzh8hSESwvKPy7o/XRV7aeqQ1T1n3Wt7yj20USZtfklVNUox3VIP+bbumx4Z3YWlTNz9a5jvi1joomvUyVV3auqL6hqnXMOhMvjZ7mj2aZpmVbsKCI+VujRLrX+zEfp9H4dyE6Jt4FpY0JYO9o0K6rKyh1F9MpJI74JunkS4mI4b0guH3y1w6byNiaIBQfTrOwurmBPSQV9m6BLKeCCIXmUVdbw/lc7mmybxjR3FhxMs7Jih7ustCmDw4nd29AhI5E3Fm5rsm0a09wd2WO1jDlGVu8spl1aAm1Sj/yu6CN5mE/vnDSmL9/JozPXkZwQe9i8V5/c9UiLZkzUsJaDaTaqampYt6uEXjlpTb7tIZ2zqFZl2Ta7MM4YsOBgmpHNe0qpqK6hd/umDw6ds5PJToln0WYLDsaABQfTjKzOL0aAnu2aPjiICEM6Z7Emv5hiu2rJGAsOpvlYk19MXlZyvX3+x8qQzpnUKCzdaq0HYyw4mGahvKqaTXv2R6RLKaBjRhI56YnWtWQMFhxMM7F+Vwk1SkQGowNc11Im63eVUFBqDwEyrZsFB9MsrMkvIS5G6NY2JaLlGNIpC8U9aMiY1syCg2kW1uQX07VtSpNMmXE4OemJ5GUmsWjzvoiWw5hIs+BgIq64vIptBWX0jmCXUrAhnbPYtLeUPSUVkS6KMRFjwcFE3Nr8YiCy4w3BBnd2jyZdbK0H04pZcDARt3pnMUnxMeRlJdefuQlkpyTQOTuZpdsKI10UYyLGgoOJuDX5xfRol0ZsjES6KAcMzMtk895S9u23riXTOllwMBG1p6SCvfsr6ZVz7B/s0xAD8zIAWLrVWg+mdfIVHETkURGZLSKTG5KnjrQOIjIz6HNXEZkhIh+KyBRxOonIZi99hojkHOkOmuZtzU433tBcBqMD2qUl0jEjyYKDabXqDQ4icikQq6qjgDwR6eMnTx1p2cATQPBp4v8A31XV04EuwGDgZOA3qjrOe+Uf7Y6a5ml1fjHpSXHkpCdGuii1DMjLYMPuEorK7IY40/r4aTmMA17w3n8IjPaZJ1xaNXAlcOB0TFXvVNWvvI9tgV3ASOBmEflURP7qb1dMtKlRZW1+Mb1y0hBpPuMNAYPyMlHgq21FkS6KMU3OT3BIBbZ47wuBDj7z1EpT1UJVDXvrqYhcCSxV1a3A28AoVT0F6CsiQ8LknyQi80RkXn6+NSyi0Y7CMkoqqptdl1JAh4xE2qYm2ER8plXyExyKgcA1hml1LBMuj5/lABCRnsCtwI+8pNmqGjhdWw7U6spS1SmqOkJVR+Tk2JBENAqMN/SK4GR7hyMiDMzLYE1+MaUV1ZEujjFNyk9wmM/BrqShwHqfefwshzcO8SxwQ1CrYpqI5IpICjABWOKjnCbKrM4vpl1aIpnJ8ZEuSp0G5rlpvJdvt4Fp07r4eYb0VGCmiOQBE4GrROReVZ18mDwjAQ2TFs7tQFfgfq/f+S7gbmA6UAE8rKorGrhfppmrqqlh/a79nNA1K9JFOaxO2clkJsezZGshJ3TNjnRxjGky9QYHVS0UkXHAWcAfVXU7sLCePAUA4dK8/OOC3v8M+FmYTfdryI6Y6BJ4JGhzmTKjLjEiDMjN4PP1eyivqiYxLjIPIjKmqfm6z0FV96rqC15g8J3Hz3KmdQo8ErS5BwdwN8RV1SgrdxRHuijGNBm7Q9pERKQfCdoQ3dulkpoQa1ctmVbFgoNpcoFHgkZDqwFc11L/3AyWby+isrom0sUxpklYcDBNLvBI0Eg+L7qhBuZlUlFVc+DyW2NaOgsOpsk1l0eCNkSv9qkkxsXYNN6m1bDgYJrcqp1FzeKRoA0RFxPDcR3T+WpbIVXWtWRagej57zQtwtZ9pewoLKdv+/RIF6XBBuZlsr+imnkb9ka6KMYccxYcTJP6aKWbB6tvx+gLDn07pBEXI7yzxK7MNi2fBQfTpD5akU9mcjwdmuEU3fVJjIuld/s03lu2A1WNdHGMOaYsOJgmU1ldwyerd9G3Q/OcotuPgXkZbNlXypItNjBtWjYLDqbJzN+wl6LyKvp2iL4upYB+HTOIjRGmLbWuJdOyWXAwTWbGinziYiRqbn4LJzUxjpO6t+EdCw6mhbPgYJrMjBU7Gd4tm6T45j9lxuFMGNiB1TuLWZNvN8SZlsuCg2kS2wpKWb69iHHHtY90UY7a2QM7AljXkmnRLDiYJvHesh0AnDUg+oNDXlYyQztnMs0uaTUtmAUH0yTeWbKdXjmp9I7Cm9/COXtgRxZuLmBbQWmki2LMMWHBwRxze0oq+GzdHiYOyo10URrNOYNc19K7S3dEuCTGHBsWHMwx9/5XO6iu0QMVakvQKyeN3u3TbNzBtFi+goOIPCois0VkckPy1JHWQURmBn2OF5E3vXw31JVmote0JdvplJXMwLyMSBelUU0Y2IHP1u1hb0lFpItiTKOrNziIyKVArKqOAvJEpI+fPHWkZQNPAKlBi/8AmOflO19E0utIM1GouLyKmat2cc6gjlF7V3RdzhmYS3WN8v5X1rVkWh4/LYdxwAve+w+B0T7zhEurBq4ECutYdjYwoo60Q4jIJBGZJyLz8vPzfeyGiYTpy3dSUV3TorqUAgZ1yqBTVjLTbNzBtEB+gkMqsMV7Xwh08JmnVpqqFqpq6IN4fS0bukFVnaKqI1R1RE5Ojo/dMJHw2oKttE9PZFjX7EgXpdGJCGcN6MDMVfmUlFdFujjGNCo/waEYSPbep9WxTLg8fpY72mVNM5ZfVM70FTu5ZFgnYmNaVpdSwISBHSmvqjkwFbkxLYWfSnc+B7uShgLrfebxs9zRLmuasalfbqG6Rrl8eOdIF+WYObF7Nm1SE+yqJdPixPnIMxWYKSJ5wETgKhG5V1UnHybPSEDDpIXzBPCWiIwBBgCf4bqUQtNMFFFVXpy/ieO7ZLWYG9/CiYuN4cz+7Xl78XYqqmpIiLNGrmkZ6v1LVtVC3ADxHGC8qi4MCQzh8hSESwvKPy7o/QbgLOAT4ExVrQ6XdhT7aCJg8ZYCVu4o5vIRLbfVEDBhYEeKyquYvWZXpItiTKPx03JAVfdy8Ooh33n8LOfl2xpm2VppJnq8OG8ziXExXDA0L9JFOeZO7d2OtMQ43lmyvUVMLGgM2ECvOQaKy6t4bcEWzhnUkYyk+EgX55hLio/ljP7tmbZ0O5XVNZEujjGNwoKDaXTPzd1IYVkV3zq1R6SL0mTOG5zL3v2VfLpmd6SLYkyjsOBgGlVFVQ2PzFzHyJ5tOL5LVqSL02RO65tDWmIcby3eFumiGNMoLDiYRvXagi1sLyzjO2N7RbooTSopPpYz+7fnHetaMi2EBQfTaGpqlH99vJb+uRmM7dv67lo/d3Au+6xrybQQFhxMo3l7yXZW7yzmO2N7trhJ9vwIdC39d5F1LZnoZ8HBNIrSimp++9ZX9OuYznmDW85DfRoiuGuposq6lkx0s+BgGsVDM1azZV8pv7pwIHGxrffP6sLj8ygoreRjm2vJRLnW+19sGs3G3ft5+OO1XDg0j5E920a6OBE1pk8ObVITmLpgS/2ZjWnGLDiYo1JTo9w5dTFxMcLPz+0f6eJEXHxsDOcNzuX9r3ZQbNN4myhmwcEclQemr2bmql3ccW5/OmYmRbo4zcJFx+dRVlnDuzZTq4liFhzMEZu1ahd/eX8lFx2fx7Und410cZqN4d2y6ZydzGsLtka6KMYcMQsO5ois31XCLc99Sa+cNH57yeBWeelqXUSEC4fmMWv1LnYVl0e6OMYcEV+zsprW55nPNtb53d6SCqbMXEtldQ3XDcm1M+QwLjmhEw/OWMPUL7dw45iekS6OMQ1mLQfTIPv2V/DIrLVUVNXw7dE9aJ9u4wzh9OmQztAuWbwwbxOqGuniGNNgFhyMb9sKSnn4ozXsr6jmW6d2Jzczuf6FWrErR3Rh5Y5iFm0uqD+zMc2Mr+AgIo+KyGwRmdyQPH7SROS7IjLDey0QkX+JSJyIbAxKH3w0O2mO3qqdRUz5eC0Ak07rSefslAiXqPk7f2guSfExPD9vU6SLYkyD1RscRORSIFZVRwF5ItLHTx6/aar6kKqO8x4dOhOYAgwBng2kq+riRttj02DzN+zhidnryU5J4LvjeluLwaeMpHjOHZTLGwu2UlphT7o10cVPy2EcBx/X+SEw2mcev2kAiEgnoIOqzgdGApeIyCwReVpEbOA8AlSV97/awctfbKFnuzQmndaTzOSW/2S3xnTFiV0oKq/i7SU2GZ+JLn6CQyoQmAugEOjgM4/ftIDvAQ957z8HxqrqaGAfcG7oBkVkkojME5F5+fk2j01jq1HltYVb+XD5ToZ1zeabo7qTFB8b6WJFnZN7tKFb25TDXv1lTHPkJzgUA4F+hLQ6lgmXx28aIhIDjFfV6d53i1Q1cKq1HKjVlaWqU1R1hKqOyMlpfc8OOJaqqmt4ef5m5q7bw2l92vG1YZ2IjbH7GI6EiHDdyG7M27CXJVtsYNpEDz/BYT4Hu3+GAut95vGbBjAG+CxofU+JyFARiQUuARb6KKdpBDU1yo+eX8CXm/Zx1oAOTBjY0W5wO0qXj+hCSkIsj89eH+miGOObn778qcBMEckDJgJXici9qjr5MHlGAuozDWAC8HHQ+u4BngEEeF1V3z+y3TMNoarc8+Yy3ly0jQkDO7bKp7kdC5nJ8XxtWGee/3wTt0/sR7u0xEgXyZh61dtyUNVC3EDyHFzXz8KQwBAuT4HfNG/5n6vqK0HrW6KqQ1R1sKreefS7afx4+KO1PD57Pd8e3YPT+rSLdHFalG+O6kZFdQ3PzbWxBxMdfN3noKp7VfUFVa1zmslwefymmcj74Ksd/OGd5Zw/JJc7z+1vXUmNrHf7dMb0acdTczbYU+JMVLA7pA2b9+7nxy8sZGBeBvddPpQYG3w+Jr49ugc7Cst55YvNkS6KMfWy4NDKVVTV8P1nvqS6Rnng6mF2ueoxNLZvDkM6Z/LAjNVUVlvrwTRvFhxaub+9v5IFm/bxx8uG0L1daqSL06KJCLec0YdNe0p59Ut7jKhp3iw4tGJLthTwr4/Xcvnwzpw7ODfSxWkVTu/XnkGdMnhg+mqqrPVgmjELDq1UZXUNP31pEW1SE5h83oBIF6fVEBF+eHofNuzezyvWejDNmAWHVurfM9eybFshv75oIJkpNl9SUzprQAeGdsnivmkrKC6vinRxjAnLgkMrtHnvfv7+/irOGdiRcwZZd1JTExF+dcEAdhaV88D01ZEujjFhWXBohX7/9nJE4BcXWHdSpJzQNZtLh3Xi0Znr2LC7JNLFMaYWCw6tzOfr9/Dmom1MOq0XnbLsuQyR9LNz+hEXK/z6zWX2KFHT7NhzElqRmhrlnjeW0TEjie+MtYfeH6nGnH57bN8c3l6yndteWsSwrtmNtt66XH1y12O+DdMyWMuhFZm6YAuLtxRw+8R+pCTYeUFzcGrvdnRvm8IbC7eyt6Qi0sUx5gALDq1ERVUNf31/JYM6ZXDh0LxIF8d4YkS4fHgXAF6cv5ka614yzYQFh1biuc83smlPKbeefZzNndTMZKcmcP6QPNbvLuH9ZTsiXRxjAAsOrcL+iir+8cFqTurRxp7R0EwN65rFid2zmbEynwWb9kW6OMZYcGgNHp+9nl3F5fx0wnE2FXczJSJcMDSPHu1SeeWLzWzasz/SRTKtnAWHFq64vIopH69l3HE5jOjeJtLFMYcRFxPD1Sd1JSM5nsdnr2d7YVmki2RaMQsOLdxTn25g3/5KbjmjT6SLYnxITYzjhlN7EB8rPDZrHflF5ZEukmmlfAUHEXlURGaLyOSG5PGTJiJxIrJRRGZ4r8Fe+t0i8rmI/PPId691219Rxb9nruW0vjmc0ATX0JvG0SY1gRtG90CBR2etZZcFCBMB9QYHEbkUiFXVUUCeiNQ6BQ2Xx28aMAR4VlXHea/FIjICGA2cBGwWkTMbbY9bkf/M2cCekgprNUSh9ulJfPvUHlTXKFNmrrUuJtPk/LQcxgEveO8/xFXafvL4TRsJXCIis0TkaRGJA04DXlY3p8D7wBi/O2Sc0opqpny8ltG92zG8m7UaolHHzCRuOq0nMQKPzFzLln2lkS6SaUX8BIdUIDDxfCHQwWcev2mfA2NVdTSwDzjXzzZFZJKIzBORefn5+T52o3V5Zu5GdhVXcMuZ1mqIZu3Tk7hpTE8SYmN4dNZaNtpVTKaJ+AkOxUBghra0OpYJl8dv2iJV3ealLQf6+Nmmqk5R1RGqOiInx67dD1ZWWc3DH63hlJ5tOdGuUIp6bdMSmXRaT1IS4njsk3Ws3VUc6SKZVsBPcJjPwa6kocB6n3n8pj0lIkNFJBa4BFjoc5umDs/N3Uh+UTk/tLGGFiMrJYFJY3qSmRzPE7PXs2pHUaSLZFo4P7OvTQVmikgeMBG4SkTuVdXJh8kzElCfaYuAZwABXlfV90UkBvidiPwdOMd7GR/KKqt56KM1nNSjDaf0ahvp4phGlJEcz01jevJ/n6zjyTkbuPqkrvTPzYh0sUwLVW/LQVULcQPJc4DxqrowJDCEy1PQgLQlqjpEVQer6p3e+mqAM4GZwERVXdcoe9sKvDh/MzsKy+0KpRYqLTGOG0f3JDcziac/28Dy7YWRLpJpoXzd56Cqe1X1BVXd3pA8ftPqWF+pqr6kqmv9lNFAeVU1D01fzfBu2YyyVkOLlZwQyw2n9iA3M5ln525koz1JzhwDdod0C/Ly/C1sLSjjljP62BxKLVxSfCzfHNWdjKR4nvh0AzvsPgjTyCw4tBCV1TU8MH01x3fJYkyfdpEujmkCaYlxfOvUHsTFCE9+up795VWRLpJpQSw4tBCvfLGZLftKrdXQyrRJTeDakd0oLKvi2c83Ul1jDwsyjcOCQwtQWV3DP6evZkjnTMYdZ/d8tDZd2qRw8fF5rMkv4Z0l2+pfwBgf7EHCUSr4IfefrdvNpj2lnH5ce56duymCpTKRMrxbG7YWlPHJmt10a5vKoE6ZkS6SiXLWcohyldU1TF++k65tUujbIT3SxTERNHFQRzpnJ/PKl5vZW1IR6eKYKGfBIcrNXbeHwrIqzhrQwcYaWrm4mBiuOrErqvD8vE02/mCOigWHKFZeVc2MFTvplZNKr5y0SBfHNANtUhO4+IRObNyzn+krdka6OCaKWXCIYp+u2U1JRTVnDegY6aKYZmRo5yyO75LFjBU7bZpvc8QsOESp0opqPl6VT7+O6XRtkxLp4phm5vwhuaQmxPHy/M1UVddEujgmCllwiFKzVudTVlnDmf3DPV7DtHYpCXFcfEIntheW8aF1L5kjYMEhCu0uLueTNbsZ1CmTvKzk+hcwrVL/3AyGdc3i45X5bN5rDwkyDWPBIQo9OGMNlVU1nNm/faSLYpq58wbnkZYYx0vWvWQayIJDlFm/q4QnP13PsK7ZtE9PinRxTDOXnBDLJSd0YmdROR8st+4l458Fhyjzu7e/Ij42hrMG2liD8ee4jhkM75bNxyvz+XLj3kgXx0QJCw5R5NM1u5m2dAffHduLjKT4SBfHRJHzBueSkRzPT15cSFlldaSLY6KABYcoUV2j3PvfZeRlJnHTaT0jXRwTZZLiY7l0WCfW5pfwp2krIl0cEwV8BQcReVREZovI5Ibk8ZMmIpki8raIvCcir4pIgojEichGEZnhvQYfzU62BM/M3cjSrYX8bGI/kuJjI10cE4X6tE/n2pFdeeyTdXy2dneki2OauXqDg4hcCsSq6iggT0RqPZw4XB6/acA1wF9U9SxgO3AOMAR4VlXHea/FjbXD0Si/qJw/vrOcUb3acuHQvEgXx0SxOyb2p0t2Cre+tJASeziQOQw/LYdxwAve+w+B0T7z+EpT1QdV9T0vLQfYCYwELhGRWSLytIjUmlpcRCaJyDwRmZefn+9jN6LXb9/6irLKau65aJBNrmeOSmpiHH+6bAib95byu7e/inRxTDPmJzikAlu894VAuMtkwuXxmwaAiJwCZKvqHOBzYKyqjgb2AeeGblBVp6jqCFUdkZPTch9wM3vNLl79cgv/c1overe3yfXM0Tu5Z1tuOLUH/5mzkZmrWvaJlTlyfoJDMRC4DTetjmXC5fGbhoi0Ae4HbvC+W6SqgUdaLQdqdWW1BiXlVdz+8mK6tknhe+N7R7o4pgW5bcJx9MxJ5acvLbJnP5iw/ASH+RzsShoKrPeZx1eaiCTgupruUNUN3ndPichQEYkFLgEW+tudluUP7yxn09793Hf5UJITbBDaNJ6k+Fj+duXx7C6u4H9fWECNPfvBhPDzmNCpwEwRyQMmAleJyL2qOvkweUYC6jPt28Bw4E4RuRN4CLgHeAYQ4HVVff9odzTazF6ziyc/3cC3Tu3OST3aRLo4pgUa0jmLX5zfn1+8tpSHPlpjrVNziHqDg6oWisg44Czgj6q6nZAz+TB5CgB8pj3kvUINafjutAwFpZXc9uIiurdN4acT+kW6OKYFu3ZkN+au38uf313BkM6ZjOlzdON3wc82j0ZXn9w10kVoNnzd56Cqe1X1BS8w+M7jN80cpKrc/vIidhSW8dcrj7fuJHNMiQi/v3Qwfdqn893/fMGyrYWRLpJpJuwO6WbmP59t5O0l27ltwnGc0DU70sUxrUBqYhyP33AiaYlxfOvxufb0OANYcGhWlmwp4NdvLmPccTncNMamyDBNJzczmcdvOJH95dVc+8hnbNpjz39o7Sw4NBM7C8u46cl55KQl8ufLhxITYze7mabVr2MGj99wIruLy7ns4dks325dTK2ZBYdmoKyymklPzWff/kqmfGM4bdMSI10k00oN79aGF75zCgBXPPwpby3eVs8SpqXycymrOYaqa5TbXlrEgk37ePjaYQzMy4x0kUwr169jBi99ZxQ3P/0FNz/9BRcdn8ddFwykTWrCEa+zukbZVVzO1n2l7C6poGB/JUXllZRX1lDpPaEuJkZIiI0hNTGOtKQ40hPjSPPeZyTFk5EcT0pCLDE+p5CprlGKy6vcqyzws5Li8ipKKqqprlFUlbjYGJITYklLjCM7JZ4+HdLp0S6V2FbeerfgEEGqyi9fW8IbC7dy+8R+nDMoN9JFMgaALm1SeOXmUTw4fQ33f7iKd5fu4LLhnfnmqO70ykk97Bxf5VXV7CgoY2tBGdsKStlWUMb2gjKqvBvtBA5U+IlxMSQnuGeTVNcoFVU1bN1XSnF5FeVVtR9rGitCelIcyQmxJMbFkhAnCHJgu2WVNZRWVlNWWR12ecALQLHExsQgAlXVNeyvcPnfW7YDgKyUeE7p2ZaxfXOYOCiXzJTW9/wUUY3+OyNHjBih8+bNi3QxGkRV+dO0FTw4Yw3fGduL2yc27H6GaL+e3ETGkVzHv2pHEf/6eC2vLdhCZbXSISOREd3bkJeZRHpSPKqwd38FO4vKmLtuD7uLKwjUKsnxseRmJZGXmUxuZhK5Wcm0S0sgLqb+Hu3K6poDZ/0FpZUUlVVSWFZFUVnlgcq8wgsAipIYF0tyfCxJ8bEkx8eQ5LUGDrZA4klLjCMhLvy2K6pqGNYti+Xbi5i7bg+zV+9ia0EZ8bHC+OPac83Ibozp3a5FjQeKyHxVHRH2OwsOTU9V+d3by5ny8Vq+flJXfntJw2dbteBgjsTR3OS1s7CMaUu3M3f9Xr7YsJc9JRWUek+VS0+Ko11aIikJsS4IeMEgMzk+qmYSDj4+qsrSrYVM/XILUxdsZVdxOT1zUrlxdE8uG965ziATTSw4NCPVNcqdry7muc838Y1TuvGrCwYe0ZmIBQdzJBr7DuDAeEF8rKsoo/3vsq7jU1FVw1uLt/HYJ+tYtLmATlnJfG9876gPEocLDtG7V1GooLSSm56cx3Ofb+IHp/fm7guPLDAY01zEx8YcCAwtWUJcDBef0InXvncqj3/rRNqlJ/LzVxcz/r4ZPDt344Eg2ZLYgHQTWb2ziElPzmfjnv38+uJBXDeyW6SLZIxpIBFh3HHtGds3hxkr8/nbeyu545XFPDRjDbec0YeLT+jUYq5yavkhP8JqapSnPl3PBfd/QmFZJc/cNNICgzFRTsQNUk/93qk8dv0I0pPi+MmLCzn7rx/xxsKtLWIKdGs5HEPrdpXwi6lLmLV6F6f1zeGPXxtCx8ykSBfLGNNIRITT+3Vg/HHtmbZ0O395byU/ePZLHpi+mu+O68W5g3OjttvNgsMxsG9/Bfd/uJonP11PQmwM9148iGtO7hpVV20YY/wTEc4ZlMtZAzry5qKt/OODVdzy3AJ+99ZyvjmqO1ef1DXq7pWw4NCItu4r5dFZ63h27kZKK6u5ckQXfnx2X9qnW2vBmNYgNka46PhOXDAkj49W5vPIrLX84Z3l/OODVXxteCcuH96FIZ0zo+JE0YLDUSoqq+TD5Tt55YstzFyVj4hw4dA8/mdsT/p1zIh08YwxERATI4zv157x/dqzbGshj32yjhfmbeY/czbSKyeVcwfncmb/DgzulNlsr1j0FRxE5FGgP/CWqt7rN09jpzUHxeVVLNq0jy837WPmqnzmrd9LVY3SKSuZm8f15qqTutA5OyXSxTTGNBMD8jK47/Kh/OL8Aby1eBtTv9zCA9NXc/+Hq2mXlsBJPdpwYvc29M/NoG+H9KOaw6ox1RscRORSIFZVR4nIgyLSR1VX1ZcHGNyYaaHbbCxV1TWUVdVQ5s3HUlZZQ0l5FflF5eQXl7OzsJydRWVs3lvK6p3FhzwIpV/HdG4c05PT+7VnRLfsZnsGYIyJvMzkeL5+Ule+flJX9pZUMH3FTmat3sVna/fw1uKDD8Zsl5ZI3w5p9MpJIyc9kbZpCbRLS6RdWgKZyQkkxsWQFB9LYnwMiXExJMTGHJNuKj8th3HAC977D4HRQGhFHS7PCY2c1ujB4YuNe7n0wdn15stOiSc3M5nh3bK56sQuDO6cyfFdsshKaR4R3hgTXbJTE7h0WGcuHdYZgO0FZazYUcTK7UWs3FHEyp3FvL5wKwWllfWu67zBuTxwzbBGL6Of4JAKbPHeFwK9feZp7LRDiMgkYJL3sVhEVvjYlyOyAVhw8GM7YNex2lYLYsfJvyY7Vtc0xUaOnWN+nKLx+DwIPHjtIUkNOU513nTlJzgUA8ne+zTC3zgXLk9jpx1CVacAU3yUv1GJyLy65iIxB9lx8s+OlT92nPxprOPk5+6M+bhuHYChwHqfeRo7zRhjTBPx03KYCswUkTxgInCViNyrqpMPk2ckoI2cZowxponU23JQ1ULcgPMcYLyqLgwJDOHyFDR22tHvaqNp8q6sKGXHyT87Vv7YcfKnUY5Ti3iegzHGmMYVnTNCGWOMOaYsOBhjjKnFgkMYIhInIhtFZIb3Giwid4vI5yLyz6B8tdJaCxHpICIzvffxIvKmiMwWkRsaktYahByrTiKyOehvK8dLf9Q7LpODlquV1hKJSKaIvC0i74nIqyKS4Pd4tJZjBHUep0PqKS9fo9RVFhzCGwI8q6rjVHUckIi7tPYkYLOInCkiI0LTIlbaJiYi2cATuJsVAX4AzFPVUcD5IpLegLQWLcyxOhn4TeBvS1Xzg6efAfJEpE+4tMjsQZO4BviLqp4FbAeuwsfxaGXHCGofp9sJqqdUdXG4eulI6yoLDuGNBC4RkVki8jRwOvCyutH794ExwGlh0lqLauBK3N3rcOj0KbOBEQ1Ia+lCj9VI4GYR+VRE/uqljaP2dDHh0lokVX1QVd/zPuYA1+LveIRLa7HCHKcqguopEYkjfL10RHWVBYfwPgfGqupoYB/ubu3g6Tw6UHuKjw5NXMaIUdXCkMuLwx0Lv2ktWphj9TYwSlVPAfqKyBDsWAEgIqcA2cAm7O+pTkHH6T0OrafOpRGPkwWH8Bap6jbv/XKOcIqPVqTRpkVpBWarapH3fjnQBztWiEgb4H7gBuzvqU4hxym0nmrUv6UWfzCP0FMiMlREYoFLcJHXpviom02L4t80EckVkRRgArCEVn6sRCQB1z10h6puwP6ewgpznELrqYU05nFSVXuFvIBBwCJgMfAbXBD9BPg7sALoES4t0uWOwHGa4f3sBiz1jsXnQKzftEjvQwSO1XjcWd4i4PteWob3j/0X4CsgM1xapPfhGB6b7wJ7gRne65t+jkdrOkZ1HKe7guspL0+j1VV2h7RPIpIMnAd8oapr60prrbx5sEYD09TrY/ebZg5c1XQW8LGqbq8rrbXwezxa8zGqS2PVVRYcjDHG1GJjDsYYY2qx4GCMMaYWCw7miIlIUqTLEEpEBopIuEfZhuaL8cY/6suX7F0N4mfbqfXnqncdXxOR7t7700SkZyOsM2L/54F98Zn3qPfVNB4/D/sxBhG5A5irqh8EJb8oIr8Efg5cAZwKDMddhz0Kdwfnc3jTIQALVLVERO7y8ueHbCYTeEdV7/C2+QzQHdgfkm8AMFFVF3oDkicHffc1IEVEngpK+0RVi7xgEAgIWcATInKR9zkOWKoH70EI+AWwFngkzDFJA95VN30DwAsicpuqLgvJ53d/Y4A/AYHpDToBw4C/Ba0rBvillzYQiFHVmSKyVVXzROR8YKeqzhWR3wGnAF1EZD/udwCwE1itqjeG2adrgGRVDbe/XYFSdVN+3Aigqo+ISHvc+OWOkPw/A1YB60UkF3geqAhZbQIwQVVLgQtEJF9Vnwndtml6FhyMX5VAtYicBdzppQ0A/gGk4G7Rvw73FL+LgBqgHCjFVcQJHPx7U+AuVX0peAMiMho4O2SbN6jq8pB8j3OwkukL/C/wf97nQPDK8n5+13stA27EXU67yvvufg5WxFm4O3NDg0MV7iaicKoC5fBaDScAV4tI4Pt/q7se3e/+Xoi7LPF67zhXAjHeHEIpwDWqukJEFgAPALcBb4nIyUCZVwHfibsqBdyz51/ETUexDBcY9+OmUDjwQBgRmY37PSnQHogVkau8r5OBy9TdbHW5d+xe9/Y9YCIu8DwWtM7uQBdV/QOAt/xpdRxHvDx/96aBeCNMkDZNzIKDqZeITMBV+KfgKpbHVfVxb4bHP+PmD8rBVbA/w1WmZ+HuEdkB/Ap3N+fr3iprgLtF5Pve5+Nx12vXAMFnjQo85p31BhuAu7Y9kOdL3J2fVwHilUdx18C/zMHKPVCZTwDWAJtx88zk4K7/3hpm91OBWhMEisg5uOvMB4jIR165/wIEAsCvgY7ABj/7KyLxwN3Al6r6S+CXIjIOVzEHlgucvc9R1akikom7dv0CXPAYjZvkr9LLfrNX9l5AvLef5d53B2bnDGr5ICKXAWmq+niYY1HtlTlcuoSkXRe8DRERrePSyJDv/gNcDDwVLq9pOhYcTL1UdZq46YDn4SqYX4vIdcBM3BwvTwCTgXXAPbgumCrgC9wZazYHZyUF93d34ExaRGYA56hqmbhpvWNVtdrLe4OqLheRi4GuqvqPkLLNBeZ6d48m41oHY1S1UETOBtap6kYvewzuTLoYdzPa48BcYICq3lfH7g/Edf/8OyT9PeBj4C3cnDYfAw8Dw1X1ZREJtJp87S9wq3e8QivZUO2A+0XkblxwuxoXoK/3vv9fXAAvAtrguvk6esul4yrybq4Ysk1V3/O6habiAmcOruVwPe5elN8FbTsB+J2I3OqtEy9fB+CvHKpXSItvnohU4m7K2o4L5jXAbty8P1/z8s3BdeVZcIgwCw6moRJwZ7iX4m7DH4m74/cdXIV0NrAAd3Y+DOgKJOECS0Aa8PNAvzVuivTXRaTGW//vgXe97/4tIiW4Crq9iJyLq+Q3quqNItINV5n0xlX2scDlXrC4GPhR0HYzve8fwJ2hfgPX2sgQkXNU9ZCpjL0z80xARaS9qu4MfKeq1V55UdX9XjdQKfAnEXkXd6Ze1oD9fQJXmd8qIicA//K+yxGRocBHqjpZVb8QkbG4INLLW1fwswyO42CXz/dxXU/Hq+oVXkVe7B3bf3i/F1R1p4iMx3UXDVXVKhH5Ey74B9uoqoFnBlzvLfu4uNlAz+UwVHW4t9xrwI9xLcuyMC2UUg7OA2QiyIKDaYgxuAplBq5y+hJ4BVe55eH6lPviplIG+AzXh97GewX0AL6DqwQEN7h6H+7MdWPIHZw3eS2HGGC6qp4TUqYtuK6ZLNy0C/figsS/gVmq+lVQ3na4WSnvwVVQZ+Cm8RhB7TNfgB/igsgWbx/DPqBIRBJUda9Xxh3AT3AVe6Dl4Gt/RSQDQFW/BE4K163kGYo7034SeFtVrw8qy1Tv53hcAMgDFnutlYB/4Fp30wMJqlruDeJPFpG3gBxVnRWy3e/iLjCodQiAW3DBJaBURNJUNXS8phNuQLwuPXBjPybC7FJWUy+vC2kibl6XM3Bn0x1wFWFXYBrub+lNYDWuEvwV7iqii3GtiUtE5BZvlcfj5lgKdOX8CFdRDsZ1C4VufwjujH+O1yeOd7YKrvL7A+4s+mlve2/iKr/TRWRg0Kp64CrWM3Gtmw9xXTI3AjNEZFjQNkd5+/ywqk4F2gaVHxHpjOvSGQI8JyKDgI+ATar6Kw5tOTRof324CBeYAc6Rg08Cm8HBCdY+AU4EFqt7YNVTwOve+82q+svQiltV/4O7yuwlXIsjVF3TKWiY797iYFcRAF7X5L7QwWZvvCXgCuCNOrZjmpC1HIwfL6jqUyLyQ9zVQMuAPwKv4ro0XsTN/Pg+biByGu5Mebyq3iUi9+Iqq/e9yn2Vd0lrHod2iWTiKpWATriz3H24SvRe3NU58cBpIvIGrkJ+APdAnf96238aV1lNAt4UkZ/iWjHluFbFFtxA7hlBYxsHeFfq3A6cG/T9dcA74p6qdSvuyqQ8YIiqbvYGin+gqgvEXa6UA5Q0cH8D24/DjQ2Epiku6FyLCyxdcZfCXh+U7zUAVQ1cRfWSd1XUj4Bvicg7wEKvtVMhIom48ZdhuMD5HLALeFxEtuAG7p9X1fW4S2JneJsKHnMQDg6CB7wJPC8ib3vdVnm430sgGNbgWnIA94jIMtzvqJOqLg49JqbpWXAw9VLVwBUuXwEPqWqliAwAblTVpSKy1PuuDHdW3hfXp3yHt9zvcWfo+bjWx58D6wvu5/cqsfODNr0M+D9VXRCU5yLcGEMq7sy/M9AT+Lqq7vP6+6fjzpjVW2cxrkJ9GteieBLX7fOu1xWUgJvh8xe48ZOLcYFjd9AxKBSR03GXirZT1TcIOsP1Br03ishwL/0dbyyiIfsb55XlDwTduyEis3BB4RFcC+QTL9gc8v8rIl/3jsVuL0D9F1eJL8J1T63wWoG34QbPb/C6k/K8Y/Z7VQ1cjfS6uJsJR+J1A6lqL8LwyvFecJp37H8MnCkiH+B+V7d7FxCA65p8yAue23H3d1yBC7ymGbCJ90zEiEiyd/NTU21PcDd4hV4a21TbP6b7G3KVV2AsJPSms4gQkThVrao/p2kuLDgYY4ypxQakjTHG1GLBwRhjTC0WHIwxxtRiwcEYY0wtFhyMMcbU8v8rqR/wgxK5HwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_dist('城镇居民家庭人均居住消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_region_dist('城镇居民家庭人均居住消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均居住消费支出(元)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>上海市</td>\n",
       "      <td>2166.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>广东省</td>\n",
       "      <td>1925.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>天津市</td>\n",
       "      <td>1615.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>福建省</td>\n",
       "      <td>1606.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>北京市</td>\n",
       "      <td>1577.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>1418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>山东省</td>\n",
       "      <td>1408.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>1384.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>河北省</td>\n",
       "      <td>1344.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>1344.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>1314.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>1276.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>山西省</td>\n",
       "      <td>1245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>1234.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>1229.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>1187.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>1182.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>1181.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>1166.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>1128.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>1126.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>四川省</td>\n",
       "      <td>1126.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>江西省</td>\n",
       "      <td>1109.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>海南省</td>\n",
       "      <td>1103.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>河南省</td>\n",
       "      <td>1080.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>青海省</td>\n",
       "      <td>923.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>910.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>898.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>890.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>云南省</td>\n",
       "      <td>835.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>726.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均居住消费支出(元)\n",
       "排名                             \n",
       "1        上海市             2166.2\n",
       "2        广东省             1925.2\n",
       "3        天津市             1615.6\n",
       "4        福建省             1606.3\n",
       "5        北京市             1577.4\n",
       "6        浙江省             1418.0\n",
       "7        山东省             1408.6\n",
       "8     内蒙古自治区             1384.5\n",
       "9        河北省             1344.5\n",
       "10       吉林省             1344.4\n",
       "11       辽宁省             1314.8\n",
       "12       重庆市             1276.0\n",
       "13       山西省             1245.0\n",
       "14       江苏省             1234.1\n",
       "15       安徽省             1229.6\n",
       "16       湖北省             1187.5\n",
       "17       湖南省             1182.3\n",
       "18   宁夏回族自治区             1181.7\n",
       "19   广西壮族自治区             1166.9\n",
       "20      黑龙江省             1128.1\n",
       "21       陕西省             1126.9\n",
       "22       四川省             1126.7\n",
       "23       江西省             1109.8\n",
       "24       海南省             1103.8\n",
       "25       河南省             1080.1\n",
       "26       青海省              923.5\n",
       "27       甘肃省              910.3\n",
       "28  新疆维吾尔自治区              898.4\n",
       "29       贵州省              890.8\n",
       "30       云南省              835.5\n",
       "31     西藏自治区              726.6"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_rank('城镇居民家庭人均居住消费支出(元)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**在居住支出方面上海2166.2元和广东1925.2元遥遥领先分列第一第二，排名第三的天津为1615.6元**\n",
    "\n",
    "**最少的是西藏、云南、贵州、新疆、甘肃、青海都低于1000元**\n",
    "\n",
    "**经济发达的省份人均居住支出高，应该是房价高，同时因为外来人口多，需要租房居住**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>house_per</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>河北省</td>\n",
       "      <td>0.130302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>山西省</td>\n",
       "      <td>0.127136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>0.115113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>福建省</td>\n",
       "      <td>0.108902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>山东省</td>\n",
       "      <td>0.107378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>0.106805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>0.105589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>江西省</td>\n",
       "      <td>0.104514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>0.104258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>广东省</td>\n",
       "      <td>0.104124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>0.103703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>0.101557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>海南省</td>\n",
       "      <td>0.101019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>0.099981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>河南省</td>\n",
       "      <td>0.099654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>0.099006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>0.098931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>天津市</td>\n",
       "      <td>0.097550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>青海省</td>\n",
       "      <td>0.096060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>0.095688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>0.095323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>上海市</td>\n",
       "      <td>0.093369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>四川省</td>\n",
       "      <td>0.093076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>0.091992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>0.088564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>0.088103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>0.085955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>0.079403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>北京市</td>\n",
       "      <td>0.079129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>云南省</td>\n",
       "      <td>0.075446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>0.075019</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  house_per\n",
       "排名                     \n",
       "1        河北省   0.130302\n",
       "2        山西省   0.127136\n",
       "3        吉林省   0.115113\n",
       "4        福建省   0.108902\n",
       "5        山东省   0.107378\n",
       "6        安徽省   0.106805\n",
       "7       黑龙江省   0.105589\n",
       "8        江西省   0.104514\n",
       "9    宁夏回族自治区   0.104258\n",
       "10       广东省   0.104124\n",
       "11       湖北省   0.103703\n",
       "12   广西壮族自治区   0.101557\n",
       "13       海南省   0.101019\n",
       "14       湖南省   0.099981\n",
       "15       河南省   0.099654\n",
       "16       辽宁省   0.099006\n",
       "17    内蒙古自治区   0.098931\n",
       "18       天津市   0.097550\n",
       "19       青海省   0.096060\n",
       "20       重庆市   0.095688\n",
       "21       陕西省   0.095323\n",
       "22       上海市   0.093369\n",
       "23       四川省   0.093076\n",
       "24       甘肃省   0.091992\n",
       "25       贵州省   0.088564\n",
       "26  新疆维吾尔自治区   0.088103\n",
       "27       江苏省   0.085955\n",
       "28       浙江省   0.079403\n",
       "29       北京市   0.079129\n",
       "30       云南省   0.075446\n",
       "31     西藏自治区   0.075019"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_per('城镇居民家庭人均居住消费支出(元)', 'house_per')\n",
    "get_rank('house_per')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从全国来看，大部分省份的城镇居民人均居住支出占比都在10%左右,最高的是河北13%，其次是12%的山西，最少的是7.5%的西藏和云南"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 城镇居民家庭人均家庭设备及用品消费支出(元)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_dist('城镇居民家庭人均家庭设备及用品消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_region_dist('城镇居民家庭人均家庭设备及用品消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均家庭设备及用品消费支出(元)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>上海市</td>\n",
       "      <td>1800.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>北京市</td>\n",
       "      <td>1377.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>广东省</td>\n",
       "      <td>1208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>天津市</td>\n",
       "      <td>1119.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>1072.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>1026.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>福建省</td>\n",
       "      <td>972.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>948.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>916.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>山东省</td>\n",
       "      <td>915.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>903.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>四川省</td>\n",
       "      <td>876.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>867.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>河南省</td>\n",
       "      <td>866.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>江西省</td>\n",
       "      <td>854.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>853.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>785.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>723.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>716.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>710.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>河北省</td>\n",
       "      <td>693.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>678.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>673.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>669.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>青海省</td>\n",
       "      <td>644.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>618.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>海南省</td>\n",
       "      <td>616.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>山西省</td>\n",
       "      <td>612.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>597.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>云南省</td>\n",
       "      <td>509.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>376.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均家庭设备及用品消费支出(元)\n",
       "排名                                  \n",
       "1        上海市                  1800.2\n",
       "2        北京市                  1377.8\n",
       "3        广东省                  1208.0\n",
       "4        天津市                  1119.9\n",
       "5        重庆市                  1072.4\n",
       "6        江苏省                  1026.3\n",
       "7        福建省                   972.2\n",
       "8     内蒙古自治区                   948.9\n",
       "9        浙江省                   916.2\n",
       "10       山东省                   915.0\n",
       "11       湖南省                   903.8\n",
       "12       四川省                   876.3\n",
       "13       湖北省                   867.3\n",
       "14       河南省                   866.7\n",
       "15       江西省                   854.6\n",
       "16   广西壮族自治区                   853.6\n",
       "17       辽宁省                   785.7\n",
       "18       陕西省                   723.7\n",
       "19   宁夏回族自治区                   716.2\n",
       "20       吉林省                   710.3\n",
       "21       河北省                   693.6\n",
       "22       安徽省                   678.8\n",
       "23       贵州省                   673.3\n",
       "24  新疆维吾尔自治区                   669.9\n",
       "25       青海省                   644.0\n",
       "26      黑龙江省                   618.8\n",
       "27       海南省                   616.3\n",
       "28       山西省                   612.6\n",
       "29       甘肃省                   597.7\n",
       "30       云南省                   509.4\n",
       "31     西藏自治区                   376.4"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_rank('城镇居民家庭人均家庭设备及用品消费支出(元)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. 上海的家庭设备消费支出以1800元最高遥遥领先，排名第二的北京1377元\n",
    "2. 大部分省份的家庭设备消费人均支出低于一千元，最少的是西藏只有376元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>device</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>江西省</td>\n",
       "      <td>0.080481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>0.080420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>河南省</td>\n",
       "      <td>0.079965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>上海市</td>\n",
       "      <td>0.077593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>0.076429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>0.075740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>0.074290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>四川省</td>\n",
       "      <td>0.072391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>0.071482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>山东省</td>\n",
       "      <td>0.069750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>北京市</td>\n",
       "      <td>0.069116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>0.067805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>天津市</td>\n",
       "      <td>0.067619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>河北省</td>\n",
       "      <td>0.067220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>青海省</td>\n",
       "      <td>0.066987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>0.066940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>福建省</td>\n",
       "      <td>0.065912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>0.065695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广东省</td>\n",
       "      <td>0.065334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>0.063188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>山西省</td>\n",
       "      <td>0.062557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>0.061217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>0.060819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>0.060402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>0.059164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>0.058961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>0.057919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>海南省</td>\n",
       "      <td>0.056403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>0.051304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>云南省</td>\n",
       "      <td>0.045999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>0.038862</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区    device\n",
       "排名                    \n",
       "1        江西省  0.080481\n",
       "2        重庆市  0.080420\n",
       "3        河南省  0.079965\n",
       "4        上海市  0.077593\n",
       "5        湖南省  0.076429\n",
       "6        湖北省  0.075740\n",
       "7    广西壮族自治区  0.074290\n",
       "8        四川省  0.072391\n",
       "9        江苏省  0.071482\n",
       "10       山东省  0.069750\n",
       "11       北京市  0.069116\n",
       "12    内蒙古自治区  0.067805\n",
       "13       天津市  0.067619\n",
       "14       河北省  0.067220\n",
       "15       青海省  0.066987\n",
       "16       贵州省  0.066940\n",
       "17       福建省  0.065912\n",
       "18  新疆维吾尔自治区  0.065695\n",
       "19       广东省  0.065334\n",
       "20   宁夏回族自治区  0.063188\n",
       "21       山西省  0.062557\n",
       "22       陕西省  0.061217\n",
       "23       吉林省  0.060819\n",
       "24       甘肃省  0.060402\n",
       "25       辽宁省  0.059164\n",
       "26       安徽省  0.058961\n",
       "27      黑龙江省  0.057919\n",
       "28       海南省  0.056403\n",
       "29       浙江省  0.051304\n",
       "30       云南省  0.045999\n",
       "31     西藏自治区  0.038862"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_per('城镇居民家庭人均家庭设备及用品消费支出(元)', 'device')\n",
    "get_rank('device')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在占总现金消费支出的比利时，江西最多达到8%，西藏最少只有3%，支出绝对值最多的上海占总现金消费的比例为7.7%"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 城镇居民家庭人均医疗保健消费支出(元)\t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_dist('城镇居民家庭人均医疗保健消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均医疗保健消费支出(元)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>北京市</td>\n",
       "      <td>1327.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>天津市</td>\n",
       "      <td>1275.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>1171.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>1126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>1079.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>1033.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>1021.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>上海市</td>\n",
       "      <td>1005.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>948.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>河南省</td>\n",
       "      <td>941.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>935.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>广东省</td>\n",
       "      <td>929.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>河北省</td>\n",
       "      <td>923.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>890.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>山东省</td>\n",
       "      <td>885.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>828.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>805.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>776.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>山西省</td>\n",
       "      <td>774.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>737.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>青海省</td>\n",
       "      <td>718.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>709.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>708.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>四川省</td>\n",
       "      <td>661.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>云南省</td>\n",
       "      <td>637.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>625.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>福建省</td>\n",
       "      <td>617.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>海南省</td>\n",
       "      <td>579.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>546.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>江西省</td>\n",
       "      <td>524.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>385.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均医疗保健消费支出(元)\n",
       "排名                               \n",
       "1        北京市               1327.2\n",
       "2        天津市               1275.6\n",
       "3        吉林省               1171.3\n",
       "4     内蒙古自治区               1126.0\n",
       "5        辽宁省               1079.8\n",
       "6        浙江省               1033.7\n",
       "7        重庆市               1021.5\n",
       "8        上海市               1005.5\n",
       "9       黑龙江省                948.4\n",
       "10       河南省                941.3\n",
       "11       陕西省                935.4\n",
       "12       广东省                929.5\n",
       "13       河北省                923.8\n",
       "14   宁夏回族自治区                890.1\n",
       "15       山东省                885.8\n",
       "16       甘肃省                828.6\n",
       "17       江苏省                805.7\n",
       "18       湖南省                776.9\n",
       "19       山西省                774.9\n",
       "20       安徽省                737.1\n",
       "21       青海省                718.8\n",
       "22       湖北省                709.6\n",
       "23  新疆维吾尔自治区                708.2\n",
       "24       四川省                661.0\n",
       "25       云南省                637.9\n",
       "26   广西壮族自治区                625.5\n",
       "27       福建省                617.4\n",
       "28       海南省                579.9\n",
       "29       贵州省                546.8\n",
       "30       江西省                524.2\n",
       "31     西藏自治区                385.6"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt_region_dist('城镇居民家庭人均医疗保健消费支出(元)')\n",
    "get_rank('城镇居民家庭人均医疗保健消费支出(元)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**西藏的人均医疗保健支出也是最少的只有385.6元，排名前八的省份都炒股一千元， 大部分省份都在700到1000元这个区间**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>medical</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>0.100291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>河北省</td>\n",
       "      <td>0.089530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>0.088769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>河南省</td>\n",
       "      <td>0.086848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>0.083736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>0.081310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>0.080460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>山西省</td>\n",
       "      <td>0.079130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>0.079124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>0.078531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>天津市</td>\n",
       "      <td>0.077021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>0.076603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>青海省</td>\n",
       "      <td>0.074768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>0.069451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>山东省</td>\n",
       "      <td>0.067525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>北京市</td>\n",
       "      <td>0.066578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>0.065698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>0.064026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>0.061968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>0.057884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>云南省</td>\n",
       "      <td>0.057603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>0.056117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>四川省</td>\n",
       "      <td>0.054605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>0.054438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>0.054363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>海南省</td>\n",
       "      <td>0.053072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>广东省</td>\n",
       "      <td>0.050272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>江西省</td>\n",
       "      <td>0.049366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>上海市</td>\n",
       "      <td>0.043340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>福建省</td>\n",
       "      <td>0.041858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>0.039812</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区   medical\n",
       "排名                    \n",
       "1        吉林省  0.100291\n",
       "2        河北省  0.089530\n",
       "3       黑龙江省  0.088769\n",
       "4        河南省  0.086848\n",
       "5        甘肃省  0.083736\n",
       "6        辽宁省  0.081310\n",
       "7     内蒙古自治区  0.080460\n",
       "8        山西省  0.079130\n",
       "9        陕西省  0.079124\n",
       "10   宁夏回族自治区  0.078531\n",
       "11       天津市  0.077021\n",
       "12       重庆市  0.076603\n",
       "13       青海省  0.074768\n",
       "14  新疆维吾尔自治区  0.069451\n",
       "15       山东省  0.067525\n",
       "16       北京市  0.066578\n",
       "17       湖南省  0.065698\n",
       "18       安徽省  0.064026\n",
       "19       湖北省  0.061968\n",
       "20       浙江省  0.057884\n",
       "21       云南省  0.057603\n",
       "22       江苏省  0.056117\n",
       "23       四川省  0.054605\n",
       "24   广西壮族自治区  0.054438\n",
       "25       贵州省  0.054363\n",
       "26       海南省  0.053072\n",
       "27       广东省  0.050272\n",
       "28       江西省  0.049366\n",
       "29       上海市  0.043340\n",
       "30       福建省  0.041858\n",
       "31     西藏自治区  0.039812"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_per('城镇居民家庭人均医疗保健消费支出(元)', 'medical')\n",
    "get_rank('medical')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**在占总现金消费支出比例方面，吉林是最多的达到10%，第二的河北占比8.9%**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 城镇居民家庭人均交通和通信消费支出(元)\t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_dist('城镇居民家庭人均交通和通信消费支出(元)')\n",
    "plt_region_dist('城镇居民家庭人均交通和通信消费支出(元)')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**在通信和交通方面，北京上海浙江广东遥遥领先于其他省份，超过3000元，上海更是超过了4000元**\n",
    "\n",
    "**云南山东福建天津超过2000元，其他省份都低于2000**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>traffic</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>0.192472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>广东省</td>\n",
       "      <td>0.184954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>云南省</td>\n",
       "      <td>0.184187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>上海市</td>\n",
       "      <td>0.175708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>0.171713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>北京市</td>\n",
       "      <td>0.171607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>海南省</td>\n",
       "      <td>0.165201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>山东省</td>\n",
       "      <td>0.163163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>福建省</td>\n",
       "      <td>0.148942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>天津市</td>\n",
       "      <td>0.148196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>0.138922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>四川省</td>\n",
       "      <td>0.138297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>山西省</td>\n",
       "      <td>0.136929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>河北省</td>\n",
       "      <td>0.135526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>0.134780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>0.133532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>0.130348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>0.127087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>河南省</td>\n",
       "      <td>0.126844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>0.126384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>0.126314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>0.123162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>江西省</td>\n",
       "      <td>0.119629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>0.117836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>0.116782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>青海省</td>\n",
       "      <td>0.116146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>0.111504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>0.108798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>0.105275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>0.103810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>0.101067</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区   traffic\n",
       "排名                    \n",
       "1        浙江省  0.192472\n",
       "2        广东省  0.184954\n",
       "3        云南省  0.184187\n",
       "4        上海市  0.175708\n",
       "5    广西壮族自治区  0.171713\n",
       "6        北京市  0.171607\n",
       "7        海南省  0.165201\n",
       "8        山东省  0.163163\n",
       "9        福建省  0.148942\n",
       "10       天津市  0.148196\n",
       "11   宁夏回族自治区  0.138922\n",
       "12       四川省  0.138297\n",
       "13       山西省  0.136929\n",
       "14       河北省  0.135526\n",
       "15       江苏省  0.134780\n",
       "16       辽宁省  0.133532\n",
       "17       湖南省  0.130348\n",
       "18     西藏自治区  0.127087\n",
       "19       河南省  0.126844\n",
       "20    内蒙古自治区  0.126384\n",
       "21       贵州省  0.126314\n",
       "22  新疆维吾尔自治区  0.123162\n",
       "23       江西省  0.119629\n",
       "24       安徽省  0.117836\n",
       "25       吉林省  0.116782\n",
       "26       青海省  0.116146\n",
       "27      黑龙江省  0.111504\n",
       "28       甘肃省  0.108798\n",
       "29       湖北省  0.105275\n",
       "30       重庆市  0.103810\n",
       "31       陕西省  0.101067"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_per('城镇居民家庭人均交通和通信消费支出(元)', 'traffic')\n",
    "get_rank('traffic')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "交通和通信方面的支出占比都超过10%，排名第一的浙江占比19.2%"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 城镇居民家庭人均文教娱乐服务消费支出(元)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_dist('城镇居民家庭人均文教娱乐服务消费支出(元)')\n",
    "plt_region_dist('城镇居民家庭人均文教娱乐服务消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均文教娱乐服务消费支出(元)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>上海市</td>\n",
       "      <td>3363.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>北京市</td>\n",
       "      <td>2901.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>2586.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>广东省</td>\n",
       "      <td>2376.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>2133.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>天津市</td>\n",
       "      <td>1899.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>福建省</td>\n",
       "      <td>1786.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>1641.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>1595.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>1495.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>1479.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>1418.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>1408.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>山东省</td>\n",
       "      <td>1401.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>1286.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>1263.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>1254.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>1244.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>1243.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>山西省</td>\n",
       "      <td>1229.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>四川省</td>\n",
       "      <td>1224.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>江西省</td>\n",
       "      <td>1179.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>河南省</td>\n",
       "      <td>1137.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>1136.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>云南省</td>\n",
       "      <td>1014.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>1012.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>海南省</td>\n",
       "      <td>1004.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>1001.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>河北省</td>\n",
       "      <td>1001.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>青海省</td>\n",
       "      <td>908.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>478.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均文教娱乐服务消费支出(元)\n",
       "排名                                 \n",
       "1        上海市                 3363.3\n",
       "2        北京市                 2901.9\n",
       "3        浙江省                 2586.1\n",
       "4        广东省                 2376.0\n",
       "5        江苏省                 2133.3\n",
       "6        天津市                 1899.5\n",
       "7        福建省                 1786.0\n",
       "8     内蒙古自治区                 1641.2\n",
       "9        陕西省                 1595.8\n",
       "10       辽宁省                 1495.9\n",
       "11       安徽省                 1479.8\n",
       "12       湖南省                 1418.9\n",
       "13       重庆市                 1408.0\n",
       "14       山东省                 1401.8\n",
       "15   宁夏回族自治区                 1286.2\n",
       "16       湖北省                 1263.2\n",
       "17       贵州省                 1254.6\n",
       "18       吉林省                 1244.6\n",
       "19   广西壮族自治区                 1243.7\n",
       "20       山西省                 1229.7\n",
       "21       四川省                 1224.7\n",
       "22       江西省                 1179.9\n",
       "23       河南省                 1137.2\n",
       "24       甘肃省                 1136.7\n",
       "25       云南省                 1014.4\n",
       "26  新疆维吾尔自治区                 1012.4\n",
       "27       海南省                 1004.6\n",
       "28      黑龙江省                 1001.5\n",
       "29       河北省                 1001.0\n",
       "30       青海省                  908.1\n",
       "31     西藏自治区                  478.0"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_rank('城镇居民家庭人均文教娱乐服务消费支出(元)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在文教娱乐方面上海北京人均支出遥遥领先，上海以3363元排名第一，北京以2901元排名第二\n",
    "\n",
    "只有上海北京浙江广东江苏在文教娱乐方面的支出超过2000元\n",
    "\n",
    "大部分省份是千元水平\n",
    "\n",
    "西藏最少478元，倒数第二的是青海908元，倒数第三的河北1001元刚刚超过1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>cultural</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>0.148584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>北京市</td>\n",
       "      <td>0.145572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>上海市</td>\n",
       "      <td>0.144967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>0.144813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>0.134987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>0.128537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>广东省</td>\n",
       "      <td>0.128505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>山西省</td>\n",
       "      <td>0.125573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>0.124733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>福建省</td>\n",
       "      <td>0.121085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>0.119988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>0.117274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>0.114872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>天津市</td>\n",
       "      <td>0.114692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>0.113478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>0.112643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>江西省</td>\n",
       "      <td>0.111115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>0.110314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>0.108241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>山东省</td>\n",
       "      <td>0.106859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>0.106567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>0.105587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>河南省</td>\n",
       "      <td>0.104922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>四川省</td>\n",
       "      <td>0.101172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>0.099283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>河北省</td>\n",
       "      <td>0.097012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>青海省</td>\n",
       "      <td>0.094458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>0.093739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>海南省</td>\n",
       "      <td>0.091940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>云南省</td>\n",
       "      <td>0.091601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>0.049352</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  cultural\n",
       "排名                    \n",
       "1        江苏省  0.148584\n",
       "2        北京市  0.145572\n",
       "3        上海市  0.144967\n",
       "4        浙江省  0.144813\n",
       "5        陕西省  0.134987\n",
       "6        安徽省  0.128537\n",
       "7        广东省  0.128505\n",
       "8        山西省  0.125573\n",
       "9        贵州省  0.124733\n",
       "10       福建省  0.121085\n",
       "11       湖南省  0.119988\n",
       "12    内蒙古自治区  0.117274\n",
       "13       甘肃省  0.114872\n",
       "14       天津市  0.114692\n",
       "15   宁夏回族自治区  0.113478\n",
       "16       辽宁省  0.112643\n",
       "17       江西省  0.111115\n",
       "18       湖北省  0.110314\n",
       "19   广西壮族自治区  0.108241\n",
       "20       山东省  0.106859\n",
       "21       吉林省  0.106567\n",
       "22       重庆市  0.105587\n",
       "23       河南省  0.104922\n",
       "24       四川省  0.101172\n",
       "25  新疆维吾尔自治区  0.099283\n",
       "26       河北省  0.097012\n",
       "27       青海省  0.094458\n",
       "28      黑龙江省  0.093739\n",
       "29       海南省  0.091940\n",
       "30       云南省  0.091601\n",
       "31     西藏自治区  0.049352"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_per('城镇居民家庭人均文教娱乐服务消费支出(元)','cultural')\n",
    "get_rank('cultural')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "江苏、北京、上海、浙江的文教娱乐支出占比达到14%，大部分省份在9%到13%之间，最少的西藏只有4.9%"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 城镇居民家庭人均其它消费支出(元)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_dist('城镇居民家庭人均其它消费支出(元)')\n",
    "plt_region_dist('城镇居民家庭人均其它消费支出(元)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均其它消费支出(元)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>上海市</td>\n",
       "      <td>1217.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>北京市</td>\n",
       "      <td>848.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>710.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>天津市</td>\n",
       "      <td>688.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>广东省</td>\n",
       "      <td>653.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>585.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>546.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>514.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>506.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>四川省</td>\n",
       "      <td>503.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>500.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>福建省</td>\n",
       "      <td>499.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>481.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>462.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>444.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>435.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>435.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>河南省</td>\n",
       "      <td>418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>山东省</td>\n",
       "      <td>415.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>402.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>402.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>河北省</td>\n",
       "      <td>395.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>387.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>372.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>江西省</td>\n",
       "      <td>345.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>青海省</td>\n",
       "      <td>332.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>山西省</td>\n",
       "      <td>331.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>328.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>306.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>云南省</td>\n",
       "      <td>285.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>海南省</td>\n",
       "      <td>284.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均其它消费支出(元)\n",
       "排名                             \n",
       "1        上海市             1217.7\n",
       "2        北京市              848.5\n",
       "3     内蒙古自治区              710.4\n",
       "4        天津市              688.7\n",
       "5        广东省              653.8\n",
       "6        辽宁省              585.8\n",
       "7        浙江省              546.4\n",
       "8        江苏省              514.4\n",
       "9        吉林省              506.1\n",
       "10       四川省              503.1\n",
       "11   宁夏回族自治区              500.1\n",
       "12       福建省              499.3\n",
       "13     西藏自治区              481.8\n",
       "14       重庆市              462.8\n",
       "15  新疆维吾尔自治区              444.2\n",
       "16       陕西省              435.7\n",
       "17       安徽省              435.6\n",
       "18       河南省              418.0\n",
       "19       山东省              415.6\n",
       "20      黑龙江省              402.7\n",
       "21       湖南省              402.5\n",
       "22       河北省              395.9\n",
       "23       甘肃省              387.5\n",
       "24       湖北省              372.9\n",
       "25       江西省              345.7\n",
       "26       青海省              332.5\n",
       "27       山西省              331.1\n",
       "28   广西壮族自治区              328.3\n",
       "29       贵州省              306.2\n",
       "30       云南省              285.0\n",
       "31       海南省              284.9"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_rank('城镇居民家庭人均其它消费支出(元)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**其他消费方面上海同样遥遥领先唯一一个超过1000，达到1217元，排名第二的北京848元**\n",
    "\n",
    "**11个省份人均支出超过500，其他省份都在500以下**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>else</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>上海市</td>\n",
       "      <td>0.052486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>0.050762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>0.049744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>0.044122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>0.044111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>0.043561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>0.043334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>北京市</td>\n",
       "      <td>0.042564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>天津市</td>\n",
       "      <td>0.041584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>四川省</td>\n",
       "      <td>0.041561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>0.039160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>河南省</td>\n",
       "      <td>0.038566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>河北省</td>\n",
       "      <td>0.038369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>0.037837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>0.037692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>0.036855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>0.035828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>广东省</td>\n",
       "      <td>0.035361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>0.034706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>青海省</td>\n",
       "      <td>0.034586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>0.034037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>福建省</td>\n",
       "      <td>0.033851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>山西省</td>\n",
       "      <td>0.033811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>0.032565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>江西省</td>\n",
       "      <td>0.032556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>山东省</td>\n",
       "      <td>0.031681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>0.030597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>0.030443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>0.028572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>海南省</td>\n",
       "      <td>0.026074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>云南省</td>\n",
       "      <td>0.025736</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区      else\n",
       "排名                    \n",
       "1        上海市  0.052486\n",
       "2     内蒙古自治区  0.050762\n",
       "3      西藏自治区  0.049744\n",
       "4    宁夏回族自治区  0.044122\n",
       "5        辽宁省  0.044111\n",
       "6   新疆维吾尔自治区  0.043561\n",
       "7        吉林省  0.043334\n",
       "8        北京市  0.042564\n",
       "9        天津市  0.041584\n",
       "10       四川省  0.041561\n",
       "11       甘肃省  0.039160\n",
       "12       河南省  0.038566\n",
       "13       河北省  0.038369\n",
       "14       安徽省  0.037837\n",
       "15      黑龙江省  0.037692\n",
       "16       陕西省  0.036855\n",
       "17       江苏省  0.035828\n",
       "18       广东省  0.035361\n",
       "19       重庆市  0.034706\n",
       "20       青海省  0.034586\n",
       "21       湖南省  0.034037\n",
       "22       福建省  0.033851\n",
       "23       山西省  0.033811\n",
       "24       湖北省  0.032565\n",
       "25       江西省  0.032556\n",
       "26       山东省  0.031681\n",
       "27       浙江省  0.030597\n",
       "28       贵州省  0.030443\n",
       "29   广西壮族自治区  0.028572\n",
       "30       海南省  0.026074\n",
       "31       云南省  0.025736"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_per('城镇居民家庭人均其它消费支出(元)', 'else')\n",
    "get_rank('else')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**在占总现金消费支出的比例上最高的上海达到5.2%，最少的云南2.5%。大部分省份在3%到5%之间**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 特征工程\n",
    "类别特征数值化， 数值特征标准化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均现金消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均食品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均衣着消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均居住消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均家庭设备及用品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均医疗保健消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均交通和通信消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均文教娱乐服务消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均其它消费支出(元)</th>\n",
       "      <th>engle</th>\n",
       "      <th>cloth_per</th>\n",
       "      <th>house_per</th>\n",
       "      <th>device</th>\n",
       "      <th>medical</th>\n",
       "      <th>traffic</th>\n",
       "      <th>cultural</th>\n",
       "      <th>else</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>北京市</td>\n",
       "      <td>19934.5</td>\n",
       "      <td>6392.9</td>\n",
       "      <td>2087.9</td>\n",
       "      <td>1577.4</td>\n",
       "      <td>1377.8</td>\n",
       "      <td>1327.2</td>\n",
       "      <td>3420.9</td>\n",
       "      <td>2901.9</td>\n",
       "      <td>848.5</td>\n",
       "      <td>0.320695</td>\n",
       "      <td>0.104738</td>\n",
       "      <td>0.079129</td>\n",
       "      <td>0.069116</td>\n",
       "      <td>0.066578</td>\n",
       "      <td>0.171607</td>\n",
       "      <td>0.145572</td>\n",
       "      <td>0.042564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>天津市</td>\n",
       "      <td>16561.8</td>\n",
       "      <td>5940.4</td>\n",
       "      <td>1567.6</td>\n",
       "      <td>1615.6</td>\n",
       "      <td>1119.9</td>\n",
       "      <td>1275.6</td>\n",
       "      <td>2454.4</td>\n",
       "      <td>1899.5</td>\n",
       "      <td>688.7</td>\n",
       "      <td>0.358681</td>\n",
       "      <td>0.094652</td>\n",
       "      <td>0.097550</td>\n",
       "      <td>0.067619</td>\n",
       "      <td>0.077021</td>\n",
       "      <td>0.148196</td>\n",
       "      <td>0.114692</td>\n",
       "      <td>0.041584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>河北省</td>\n",
       "      <td>10318.3</td>\n",
       "      <td>3335.2</td>\n",
       "      <td>1225.9</td>\n",
       "      <td>1344.5</td>\n",
       "      <td>693.6</td>\n",
       "      <td>923.8</td>\n",
       "      <td>1398.4</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>395.9</td>\n",
       "      <td>0.323232</td>\n",
       "      <td>0.118808</td>\n",
       "      <td>0.130302</td>\n",
       "      <td>0.067220</td>\n",
       "      <td>0.089530</td>\n",
       "      <td>0.135526</td>\n",
       "      <td>0.097012</td>\n",
       "      <td>0.038369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>山西省</td>\n",
       "      <td>9792.7</td>\n",
       "      <td>3052.6</td>\n",
       "      <td>1205.9</td>\n",
       "      <td>1245.0</td>\n",
       "      <td>612.6</td>\n",
       "      <td>774.9</td>\n",
       "      <td>1340.9</td>\n",
       "      <td>1229.7</td>\n",
       "      <td>331.1</td>\n",
       "      <td>0.311722</td>\n",
       "      <td>0.123143</td>\n",
       "      <td>0.127136</td>\n",
       "      <td>0.062557</td>\n",
       "      <td>0.079130</td>\n",
       "      <td>0.136929</td>\n",
       "      <td>0.125573</td>\n",
       "      <td>0.033811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>13994.6</td>\n",
       "      <td>4211.5</td>\n",
       "      <td>2203.6</td>\n",
       "      <td>1384.5</td>\n",
       "      <td>948.9</td>\n",
       "      <td>1126.0</td>\n",
       "      <td>1768.7</td>\n",
       "      <td>1641.2</td>\n",
       "      <td>710.4</td>\n",
       "      <td>0.300938</td>\n",
       "      <td>0.157461</td>\n",
       "      <td>0.098931</td>\n",
       "      <td>0.067805</td>\n",
       "      <td>0.080460</td>\n",
       "      <td>0.126384</td>\n",
       "      <td>0.117274</td>\n",
       "      <td>0.050762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>13280.0</td>\n",
       "      <td>4658.0</td>\n",
       "      <td>1586.8</td>\n",
       "      <td>1314.8</td>\n",
       "      <td>785.7</td>\n",
       "      <td>1079.8</td>\n",
       "      <td>1773.3</td>\n",
       "      <td>1495.9</td>\n",
       "      <td>585.8</td>\n",
       "      <td>0.350753</td>\n",
       "      <td>0.119488</td>\n",
       "      <td>0.099006</td>\n",
       "      <td>0.059164</td>\n",
       "      <td>0.081310</td>\n",
       "      <td>0.133532</td>\n",
       "      <td>0.112643</td>\n",
       "      <td>0.044111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>11679.0</td>\n",
       "      <td>3767.9</td>\n",
       "      <td>1570.7</td>\n",
       "      <td>1344.4</td>\n",
       "      <td>710.3</td>\n",
       "      <td>1171.3</td>\n",
       "      <td>1363.9</td>\n",
       "      <td>1244.6</td>\n",
       "      <td>506.1</td>\n",
       "      <td>0.322622</td>\n",
       "      <td>0.134489</td>\n",
       "      <td>0.115113</td>\n",
       "      <td>0.060819</td>\n",
       "      <td>0.100291</td>\n",
       "      <td>0.116782</td>\n",
       "      <td>0.106567</td>\n",
       "      <td>0.043334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>10683.9</td>\n",
       "      <td>3784.7</td>\n",
       "      <td>1608.4</td>\n",
       "      <td>1128.1</td>\n",
       "      <td>618.8</td>\n",
       "      <td>948.4</td>\n",
       "      <td>1191.3</td>\n",
       "      <td>1001.5</td>\n",
       "      <td>402.7</td>\n",
       "      <td>0.354243</td>\n",
       "      <td>0.150544</td>\n",
       "      <td>0.105589</td>\n",
       "      <td>0.057919</td>\n",
       "      <td>0.088769</td>\n",
       "      <td>0.111504</td>\n",
       "      <td>0.093739</td>\n",
       "      <td>0.037692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>上海市</td>\n",
       "      <td>23200.4</td>\n",
       "      <td>7777.0</td>\n",
       "      <td>1794.1</td>\n",
       "      <td>2166.2</td>\n",
       "      <td>1800.2</td>\n",
       "      <td>1005.5</td>\n",
       "      <td>4076.5</td>\n",
       "      <td>3363.3</td>\n",
       "      <td>1217.7</td>\n",
       "      <td>0.335210</td>\n",
       "      <td>0.077331</td>\n",
       "      <td>0.093369</td>\n",
       "      <td>0.077593</td>\n",
       "      <td>0.043340</td>\n",
       "      <td>0.175708</td>\n",
       "      <td>0.144967</td>\n",
       "      <td>0.052486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>14357.5</td>\n",
       "      <td>5243.1</td>\n",
       "      <td>1465.5</td>\n",
       "      <td>1234.1</td>\n",
       "      <td>1026.3</td>\n",
       "      <td>805.7</td>\n",
       "      <td>1935.1</td>\n",
       "      <td>2133.3</td>\n",
       "      <td>514.4</td>\n",
       "      <td>0.365182</td>\n",
       "      <td>0.102072</td>\n",
       "      <td>0.085955</td>\n",
       "      <td>0.071482</td>\n",
       "      <td>0.056117</td>\n",
       "      <td>0.134780</td>\n",
       "      <td>0.148584</td>\n",
       "      <td>0.035828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>17858.2</td>\n",
       "      <td>6118.5</td>\n",
       "      <td>1802.3</td>\n",
       "      <td>1418.0</td>\n",
       "      <td>916.2</td>\n",
       "      <td>1033.7</td>\n",
       "      <td>3437.2</td>\n",
       "      <td>2586.1</td>\n",
       "      <td>546.4</td>\n",
       "      <td>0.342616</td>\n",
       "      <td>0.100923</td>\n",
       "      <td>0.079403</td>\n",
       "      <td>0.051304</td>\n",
       "      <td>0.057884</td>\n",
       "      <td>0.192472</td>\n",
       "      <td>0.144813</td>\n",
       "      <td>0.030597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>11512.6</td>\n",
       "      <td>4369.6</td>\n",
       "      <td>1225.6</td>\n",
       "      <td>1229.6</td>\n",
       "      <td>678.8</td>\n",
       "      <td>737.1</td>\n",
       "      <td>1356.6</td>\n",
       "      <td>1479.8</td>\n",
       "      <td>435.6</td>\n",
       "      <td>0.379549</td>\n",
       "      <td>0.106457</td>\n",
       "      <td>0.106805</td>\n",
       "      <td>0.058961</td>\n",
       "      <td>0.064026</td>\n",
       "      <td>0.117836</td>\n",
       "      <td>0.128537</td>\n",
       "      <td>0.037837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>福建省</td>\n",
       "      <td>14750.0</td>\n",
       "      <td>5790.7</td>\n",
       "      <td>1281.3</td>\n",
       "      <td>1606.3</td>\n",
       "      <td>972.2</td>\n",
       "      <td>617.4</td>\n",
       "      <td>2196.9</td>\n",
       "      <td>1786.0</td>\n",
       "      <td>499.3</td>\n",
       "      <td>0.392590</td>\n",
       "      <td>0.086868</td>\n",
       "      <td>0.108902</td>\n",
       "      <td>0.065912</td>\n",
       "      <td>0.041858</td>\n",
       "      <td>0.148942</td>\n",
       "      <td>0.121085</td>\n",
       "      <td>0.033851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>江西省</td>\n",
       "      <td>10618.7</td>\n",
       "      <td>4195.4</td>\n",
       "      <td>1138.8</td>\n",
       "      <td>1109.8</td>\n",
       "      <td>854.6</td>\n",
       "      <td>524.2</td>\n",
       "      <td>1270.3</td>\n",
       "      <td>1179.9</td>\n",
       "      <td>345.7</td>\n",
       "      <td>0.395095</td>\n",
       "      <td>0.107245</td>\n",
       "      <td>0.104514</td>\n",
       "      <td>0.080481</td>\n",
       "      <td>0.049366</td>\n",
       "      <td>0.119629</td>\n",
       "      <td>0.111115</td>\n",
       "      <td>0.032556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>山东省</td>\n",
       "      <td>13118.2</td>\n",
       "      <td>4205.9</td>\n",
       "      <td>1745.2</td>\n",
       "      <td>1408.6</td>\n",
       "      <td>915.0</td>\n",
       "      <td>885.8</td>\n",
       "      <td>2140.4</td>\n",
       "      <td>1401.8</td>\n",
       "      <td>415.6</td>\n",
       "      <td>0.320616</td>\n",
       "      <td>0.133037</td>\n",
       "      <td>0.107378</td>\n",
       "      <td>0.069750</td>\n",
       "      <td>0.067525</td>\n",
       "      <td>0.163163</td>\n",
       "      <td>0.106859</td>\n",
       "      <td>0.031681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>河南省</td>\n",
       "      <td>10838.5</td>\n",
       "      <td>3575.8</td>\n",
       "      <td>1444.6</td>\n",
       "      <td>1080.1</td>\n",
       "      <td>866.7</td>\n",
       "      <td>941.3</td>\n",
       "      <td>1374.8</td>\n",
       "      <td>1137.2</td>\n",
       "      <td>418.0</td>\n",
       "      <td>0.329917</td>\n",
       "      <td>0.133284</td>\n",
       "      <td>0.099654</td>\n",
       "      <td>0.079965</td>\n",
       "      <td>0.086848</td>\n",
       "      <td>0.126844</td>\n",
       "      <td>0.104922</td>\n",
       "      <td>0.038566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>11451.0</td>\n",
       "      <td>4429.3</td>\n",
       "      <td>1415.7</td>\n",
       "      <td>1187.5</td>\n",
       "      <td>867.3</td>\n",
       "      <td>709.6</td>\n",
       "      <td>1205.5</td>\n",
       "      <td>1263.2</td>\n",
       "      <td>372.9</td>\n",
       "      <td>0.386805</td>\n",
       "      <td>0.123631</td>\n",
       "      <td>0.103703</td>\n",
       "      <td>0.075740</td>\n",
       "      <td>0.061968</td>\n",
       "      <td>0.105275</td>\n",
       "      <td>0.110314</td>\n",
       "      <td>0.032565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>11825.3</td>\n",
       "      <td>4322.1</td>\n",
       "      <td>1277.5</td>\n",
       "      <td>1182.3</td>\n",
       "      <td>903.8</td>\n",
       "      <td>776.9</td>\n",
       "      <td>1541.4</td>\n",
       "      <td>1418.9</td>\n",
       "      <td>402.5</td>\n",
       "      <td>0.365496</td>\n",
       "      <td>0.108031</td>\n",
       "      <td>0.099981</td>\n",
       "      <td>0.076429</td>\n",
       "      <td>0.065698</td>\n",
       "      <td>0.130348</td>\n",
       "      <td>0.119988</td>\n",
       "      <td>0.034037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>广东省</td>\n",
       "      <td>18489.5</td>\n",
       "      <td>6746.6</td>\n",
       "      <td>1230.7</td>\n",
       "      <td>1925.2</td>\n",
       "      <td>1208.0</td>\n",
       "      <td>929.5</td>\n",
       "      <td>3419.7</td>\n",
       "      <td>2376.0</td>\n",
       "      <td>653.8</td>\n",
       "      <td>0.364888</td>\n",
       "      <td>0.066562</td>\n",
       "      <td>0.104124</td>\n",
       "      <td>0.065334</td>\n",
       "      <td>0.050272</td>\n",
       "      <td>0.184954</td>\n",
       "      <td>0.128505</td>\n",
       "      <td>0.035361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>11490.1</td>\n",
       "      <td>4372.8</td>\n",
       "      <td>926.4</td>\n",
       "      <td>1166.9</td>\n",
       "      <td>853.6</td>\n",
       "      <td>625.5</td>\n",
       "      <td>1973.0</td>\n",
       "      <td>1243.7</td>\n",
       "      <td>328.3</td>\n",
       "      <td>0.380571</td>\n",
       "      <td>0.080626</td>\n",
       "      <td>0.101557</td>\n",
       "      <td>0.074290</td>\n",
       "      <td>0.054438</td>\n",
       "      <td>0.171713</td>\n",
       "      <td>0.108241</td>\n",
       "      <td>0.028572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>海南省</td>\n",
       "      <td>10926.7</td>\n",
       "      <td>4896.0</td>\n",
       "      <td>636.1</td>\n",
       "      <td>1103.8</td>\n",
       "      <td>616.3</td>\n",
       "      <td>579.9</td>\n",
       "      <td>1805.1</td>\n",
       "      <td>1004.6</td>\n",
       "      <td>284.9</td>\n",
       "      <td>0.448077</td>\n",
       "      <td>0.058215</td>\n",
       "      <td>0.101019</td>\n",
       "      <td>0.056403</td>\n",
       "      <td>0.053072</td>\n",
       "      <td>0.165201</td>\n",
       "      <td>0.091940</td>\n",
       "      <td>0.026074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>13335.0</td>\n",
       "      <td>5012.6</td>\n",
       "      <td>1697.6</td>\n",
       "      <td>1276.0</td>\n",
       "      <td>1072.4</td>\n",
       "      <td>1021.5</td>\n",
       "      <td>1384.3</td>\n",
       "      <td>1408.0</td>\n",
       "      <td>462.8</td>\n",
       "      <td>0.375898</td>\n",
       "      <td>0.127304</td>\n",
       "      <td>0.095688</td>\n",
       "      <td>0.080420</td>\n",
       "      <td>0.076603</td>\n",
       "      <td>0.103810</td>\n",
       "      <td>0.105587</td>\n",
       "      <td>0.034706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>四川省</td>\n",
       "      <td>12105.1</td>\n",
       "      <td>4779.6</td>\n",
       "      <td>1259.5</td>\n",
       "      <td>1126.7</td>\n",
       "      <td>876.3</td>\n",
       "      <td>661.0</td>\n",
       "      <td>1674.1</td>\n",
       "      <td>1224.7</td>\n",
       "      <td>503.1</td>\n",
       "      <td>0.394842</td>\n",
       "      <td>0.104047</td>\n",
       "      <td>0.093076</td>\n",
       "      <td>0.072391</td>\n",
       "      <td>0.054605</td>\n",
       "      <td>0.138297</td>\n",
       "      <td>0.101172</td>\n",
       "      <td>0.041561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>10058.3</td>\n",
       "      <td>4013.7</td>\n",
       "      <td>1102.4</td>\n",
       "      <td>890.8</td>\n",
       "      <td>673.3</td>\n",
       "      <td>546.8</td>\n",
       "      <td>1270.5</td>\n",
       "      <td>1254.6</td>\n",
       "      <td>306.2</td>\n",
       "      <td>0.399044</td>\n",
       "      <td>0.109601</td>\n",
       "      <td>0.088564</td>\n",
       "      <td>0.066940</td>\n",
       "      <td>0.054363</td>\n",
       "      <td>0.126314</td>\n",
       "      <td>0.124733</td>\n",
       "      <td>0.030443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>云南省</td>\n",
       "      <td>11074.1</td>\n",
       "      <td>4593.5</td>\n",
       "      <td>1158.8</td>\n",
       "      <td>835.5</td>\n",
       "      <td>509.4</td>\n",
       "      <td>637.9</td>\n",
       "      <td>2039.7</td>\n",
       "      <td>1014.4</td>\n",
       "      <td>285.0</td>\n",
       "      <td>0.414797</td>\n",
       "      <td>0.104641</td>\n",
       "      <td>0.075446</td>\n",
       "      <td>0.045999</td>\n",
       "      <td>0.057603</td>\n",
       "      <td>0.184187</td>\n",
       "      <td>0.091601</td>\n",
       "      <td>0.025736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>9685.5</td>\n",
       "      <td>4847.6</td>\n",
       "      <td>1158.6</td>\n",
       "      <td>726.6</td>\n",
       "      <td>376.4</td>\n",
       "      <td>385.6</td>\n",
       "      <td>1230.9</td>\n",
       "      <td>478.0</td>\n",
       "      <td>481.8</td>\n",
       "      <td>0.500501</td>\n",
       "      <td>0.119622</td>\n",
       "      <td>0.075019</td>\n",
       "      <td>0.038862</td>\n",
       "      <td>0.039812</td>\n",
       "      <td>0.127087</td>\n",
       "      <td>0.049352</td>\n",
       "      <td>0.049744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>11821.9</td>\n",
       "      <td>4381.4</td>\n",
       "      <td>1428.2</td>\n",
       "      <td>1126.9</td>\n",
       "      <td>723.7</td>\n",
       "      <td>935.4</td>\n",
       "      <td>1194.8</td>\n",
       "      <td>1595.8</td>\n",
       "      <td>435.7</td>\n",
       "      <td>0.370617</td>\n",
       "      <td>0.120810</td>\n",
       "      <td>0.095323</td>\n",
       "      <td>0.061217</td>\n",
       "      <td>0.079124</td>\n",
       "      <td>0.101067</td>\n",
       "      <td>0.134987</td>\n",
       "      <td>0.036855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>9895.4</td>\n",
       "      <td>3702.2</td>\n",
       "      <td>1255.7</td>\n",
       "      <td>910.3</td>\n",
       "      <td>597.7</td>\n",
       "      <td>828.6</td>\n",
       "      <td>1076.6</td>\n",
       "      <td>1136.7</td>\n",
       "      <td>387.5</td>\n",
       "      <td>0.374133</td>\n",
       "      <td>0.126897</td>\n",
       "      <td>0.091992</td>\n",
       "      <td>0.060402</td>\n",
       "      <td>0.083736</td>\n",
       "      <td>0.108798</td>\n",
       "      <td>0.114872</td>\n",
       "      <td>0.039160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>青海省</td>\n",
       "      <td>9613.8</td>\n",
       "      <td>3784.8</td>\n",
       "      <td>1185.6</td>\n",
       "      <td>923.5</td>\n",
       "      <td>644.0</td>\n",
       "      <td>718.8</td>\n",
       "      <td>1116.6</td>\n",
       "      <td>908.1</td>\n",
       "      <td>332.5</td>\n",
       "      <td>0.393684</td>\n",
       "      <td>0.123323</td>\n",
       "      <td>0.096060</td>\n",
       "      <td>0.066987</td>\n",
       "      <td>0.074768</td>\n",
       "      <td>0.116146</td>\n",
       "      <td>0.094458</td>\n",
       "      <td>0.034586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>11334.4</td>\n",
       "      <td>3768.1</td>\n",
       "      <td>1417.5</td>\n",
       "      <td>1181.7</td>\n",
       "      <td>716.2</td>\n",
       "      <td>890.1</td>\n",
       "      <td>1574.6</td>\n",
       "      <td>1286.2</td>\n",
       "      <td>500.1</td>\n",
       "      <td>0.332448</td>\n",
       "      <td>0.125062</td>\n",
       "      <td>0.104258</td>\n",
       "      <td>0.063188</td>\n",
       "      <td>0.078531</td>\n",
       "      <td>0.138922</td>\n",
       "      <td>0.113478</td>\n",
       "      <td>0.044122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>10197.1</td>\n",
       "      <td>3694.8</td>\n",
       "      <td>1513.4</td>\n",
       "      <td>898.4</td>\n",
       "      <td>669.9</td>\n",
       "      <td>708.2</td>\n",
       "      <td>1255.9</td>\n",
       "      <td>1012.4</td>\n",
       "      <td>444.2</td>\n",
       "      <td>0.362338</td>\n",
       "      <td>0.148415</td>\n",
       "      <td>0.088103</td>\n",
       "      <td>0.065695</td>\n",
       "      <td>0.069451</td>\n",
       "      <td>0.123162</td>\n",
       "      <td>0.099283</td>\n",
       "      <td>0.043561</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均现金消费支出(元)  城镇居民家庭人均食品消费支出(元)  城镇居民家庭人均衣着消费支出(元)  \\\n",
       "0        北京市            19934.5             6392.9             2087.9   \n",
       "1        天津市            16561.8             5940.4             1567.6   \n",
       "2        河北省            10318.3             3335.2             1225.9   \n",
       "3        山西省             9792.7             3052.6             1205.9   \n",
       "4     内蒙古自治区            13994.6             4211.5             2203.6   \n",
       "5        辽宁省            13280.0             4658.0             1586.8   \n",
       "6        吉林省            11679.0             3767.9             1570.7   \n",
       "7       黑龙江省            10683.9             3784.7             1608.4   \n",
       "8        上海市            23200.4             7777.0             1794.1   \n",
       "9        江苏省            14357.5             5243.1             1465.5   \n",
       "10       浙江省            17858.2             6118.5             1802.3   \n",
       "11       安徽省            11512.6             4369.6             1225.6   \n",
       "12       福建省            14750.0             5790.7             1281.3   \n",
       "13       江西省            10618.7             4195.4             1138.8   \n",
       "14       山东省            13118.2             4205.9             1745.2   \n",
       "15       河南省            10838.5             3575.8             1444.6   \n",
       "16       湖北省            11451.0             4429.3             1415.7   \n",
       "17       湖南省            11825.3             4322.1             1277.5   \n",
       "18       广东省            18489.5             6746.6             1230.7   \n",
       "19   广西壮族自治区            11490.1             4372.8              926.4   \n",
       "20       海南省            10926.7             4896.0              636.1   \n",
       "21       重庆市            13335.0             5012.6             1697.6   \n",
       "22       四川省            12105.1             4779.6             1259.5   \n",
       "23       贵州省            10058.3             4013.7             1102.4   \n",
       "24       云南省            11074.1             4593.5             1158.8   \n",
       "25     西藏自治区             9685.5             4847.6             1158.6   \n",
       "26       陕西省            11821.9             4381.4             1428.2   \n",
       "27       甘肃省             9895.4             3702.2             1255.7   \n",
       "28       青海省             9613.8             3784.8             1185.6   \n",
       "29   宁夏回族自治区            11334.4             3768.1             1417.5   \n",
       "30  新疆维吾尔自治区            10197.1             3694.8             1513.4   \n",
       "\n",
       "    城镇居民家庭人均居住消费支出(元)  城镇居民家庭人均家庭设备及用品消费支出(元)  城镇居民家庭人均医疗保健消费支出(元)  \\\n",
       "0              1577.4                  1377.8               1327.2   \n",
       "1              1615.6                  1119.9               1275.6   \n",
       "2              1344.5                   693.6                923.8   \n",
       "3              1245.0                   612.6                774.9   \n",
       "4              1384.5                   948.9               1126.0   \n",
       "5              1314.8                   785.7               1079.8   \n",
       "6              1344.4                   710.3               1171.3   \n",
       "7              1128.1                   618.8                948.4   \n",
       "8              2166.2                  1800.2               1005.5   \n",
       "9              1234.1                  1026.3                805.7   \n",
       "10             1418.0                   916.2               1033.7   \n",
       "11             1229.6                   678.8                737.1   \n",
       "12             1606.3                   972.2                617.4   \n",
       "13             1109.8                   854.6                524.2   \n",
       "14             1408.6                   915.0                885.8   \n",
       "15             1080.1                   866.7                941.3   \n",
       "16             1187.5                   867.3                709.6   \n",
       "17             1182.3                   903.8                776.9   \n",
       "18             1925.2                  1208.0                929.5   \n",
       "19             1166.9                   853.6                625.5   \n",
       "20             1103.8                   616.3                579.9   \n",
       "21             1276.0                  1072.4               1021.5   \n",
       "22             1126.7                   876.3                661.0   \n",
       "23              890.8                   673.3                546.8   \n",
       "24              835.5                   509.4                637.9   \n",
       "25              726.6                   376.4                385.6   \n",
       "26             1126.9                   723.7                935.4   \n",
       "27              910.3                   597.7                828.6   \n",
       "28              923.5                   644.0                718.8   \n",
       "29             1181.7                   716.2                890.1   \n",
       "30              898.4                   669.9                708.2   \n",
       "\n",
       "    城镇居民家庭人均交通和通信消费支出(元)  城镇居民家庭人均文教娱乐服务消费支出(元)  城镇居民家庭人均其它消费支出(元)     engle  \\\n",
       "0                 3420.9                 2901.9              848.5  0.320695   \n",
       "1                 2454.4                 1899.5              688.7  0.358681   \n",
       "2                 1398.4                 1001.0              395.9  0.323232   \n",
       "3                 1340.9                 1229.7              331.1  0.311722   \n",
       "4                 1768.7                 1641.2              710.4  0.300938   \n",
       "5                 1773.3                 1495.9              585.8  0.350753   \n",
       "6                 1363.9                 1244.6              506.1  0.322622   \n",
       "7                 1191.3                 1001.5              402.7  0.354243   \n",
       "8                 4076.5                 3363.3             1217.7  0.335210   \n",
       "9                 1935.1                 2133.3              514.4  0.365182   \n",
       "10                3437.2                 2586.1              546.4  0.342616   \n",
       "11                1356.6                 1479.8              435.6  0.379549   \n",
       "12                2196.9                 1786.0              499.3  0.392590   \n",
       "13                1270.3                 1179.9              345.7  0.395095   \n",
       "14                2140.4                 1401.8              415.6  0.320616   \n",
       "15                1374.8                 1137.2              418.0  0.329917   \n",
       "16                1205.5                 1263.2              372.9  0.386805   \n",
       "17                1541.4                 1418.9              402.5  0.365496   \n",
       "18                3419.7                 2376.0              653.8  0.364888   \n",
       "19                1973.0                 1243.7              328.3  0.380571   \n",
       "20                1805.1                 1004.6              284.9  0.448077   \n",
       "21                1384.3                 1408.0              462.8  0.375898   \n",
       "22                1674.1                 1224.7              503.1  0.394842   \n",
       "23                1270.5                 1254.6              306.2  0.399044   \n",
       "24                2039.7                 1014.4              285.0  0.414797   \n",
       "25                1230.9                  478.0              481.8  0.500501   \n",
       "26                1194.8                 1595.8              435.7  0.370617   \n",
       "27                1076.6                 1136.7              387.5  0.374133   \n",
       "28                1116.6                  908.1              332.5  0.393684   \n",
       "29                1574.6                 1286.2              500.1  0.332448   \n",
       "30                1255.9                 1012.4              444.2  0.362338   \n",
       "\n",
       "    cloth_per  house_per    device   medical   traffic  cultural      else  \n",
       "0    0.104738   0.079129  0.069116  0.066578  0.171607  0.145572  0.042564  \n",
       "1    0.094652   0.097550  0.067619  0.077021  0.148196  0.114692  0.041584  \n",
       "2    0.118808   0.130302  0.067220  0.089530  0.135526  0.097012  0.038369  \n",
       "3    0.123143   0.127136  0.062557  0.079130  0.136929  0.125573  0.033811  \n",
       "4    0.157461   0.098931  0.067805  0.080460  0.126384  0.117274  0.050762  \n",
       "5    0.119488   0.099006  0.059164  0.081310  0.133532  0.112643  0.044111  \n",
       "6    0.134489   0.115113  0.060819  0.100291  0.116782  0.106567  0.043334  \n",
       "7    0.150544   0.105589  0.057919  0.088769  0.111504  0.093739  0.037692  \n",
       "8    0.077331   0.093369  0.077593  0.043340  0.175708  0.144967  0.052486  \n",
       "9    0.102072   0.085955  0.071482  0.056117  0.134780  0.148584  0.035828  \n",
       "10   0.100923   0.079403  0.051304  0.057884  0.192472  0.144813  0.030597  \n",
       "11   0.106457   0.106805  0.058961  0.064026  0.117836  0.128537  0.037837  \n",
       "12   0.086868   0.108902  0.065912  0.041858  0.148942  0.121085  0.033851  \n",
       "13   0.107245   0.104514  0.080481  0.049366  0.119629  0.111115  0.032556  \n",
       "14   0.133037   0.107378  0.069750  0.067525  0.163163  0.106859  0.031681  \n",
       "15   0.133284   0.099654  0.079965  0.086848  0.126844  0.104922  0.038566  \n",
       "16   0.123631   0.103703  0.075740  0.061968  0.105275  0.110314  0.032565  \n",
       "17   0.108031   0.099981  0.076429  0.065698  0.130348  0.119988  0.034037  \n",
       "18   0.066562   0.104124  0.065334  0.050272  0.184954  0.128505  0.035361  \n",
       "19   0.080626   0.101557  0.074290  0.054438  0.171713  0.108241  0.028572  \n",
       "20   0.058215   0.101019  0.056403  0.053072  0.165201  0.091940  0.026074  \n",
       "21   0.127304   0.095688  0.080420  0.076603  0.103810  0.105587  0.034706  \n",
       "22   0.104047   0.093076  0.072391  0.054605  0.138297  0.101172  0.041561  \n",
       "23   0.109601   0.088564  0.066940  0.054363  0.126314  0.124733  0.030443  \n",
       "24   0.104641   0.075446  0.045999  0.057603  0.184187  0.091601  0.025736  \n",
       "25   0.119622   0.075019  0.038862  0.039812  0.127087  0.049352  0.049744  \n",
       "26   0.120810   0.095323  0.061217  0.079124  0.101067  0.134987  0.036855  \n",
       "27   0.126897   0.091992  0.060402  0.083736  0.108798  0.114872  0.039160  \n",
       "28   0.123323   0.096060  0.066987  0.074768  0.116146  0.094458  0.034586  \n",
       "29   0.125062   0.104258  0.063188  0.078531  0.138922  0.113478  0.044122  \n",
       "30   0.148415   0.088103  0.065695  0.069451  0.123162  0.099283  0.043561  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler, LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = df.copy(deep=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.iloc[:,1:10] = StandardScaler().fit_transform(train.iloc[:,1:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>城镇居民家庭人均现金消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均食品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均衣着消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均居住消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均家庭设备及用品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均医疗保健消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均交通和通信消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均文教娱乐服务消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均其它消费支出(元)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "      <td>3.100000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-4.476706e-16</td>\n",
       "      <td>5.372047e-17</td>\n",
       "      <td>7.735748e-16</td>\n",
       "      <td>-4.154383e-16</td>\n",
       "      <td>-5.192979e-16</td>\n",
       "      <td>-1.432546e-17</td>\n",
       "      <td>1.719055e-16</td>\n",
       "      <td>1.575800e-16</td>\n",
       "      <td>-1.298245e-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.016530e+00</td>\n",
       "      <td>1.016530e+00</td>\n",
       "      <td>1.016530e+00</td>\n",
       "      <td>1.016530e+00</td>\n",
       "      <td>1.016530e+00</td>\n",
       "      <td>1.016530e+00</td>\n",
       "      <td>1.016530e+00</td>\n",
       "      <td>1.016530e+00</td>\n",
       "      <td>1.016530e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-9.699876e-01</td>\n",
       "      <td>-1.499903e+00</td>\n",
       "      <td>-2.429229e+00</td>\n",
       "      <td>-1.728744e+00</td>\n",
       "      <td>-1.727060e+00</td>\n",
       "      <td>-2.064318e+00</td>\n",
       "      <td>-9.577224e-01</td>\n",
       "      <td>-1.657557e+00</td>\n",
       "      <td>-1.079172e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-6.509137e-01</td>\n",
       "      <td>-8.070432e-01</td>\n",
       "      <td>-6.027281e-01</td>\n",
       "      <td>-4.666843e-01</td>\n",
       "      <td>-6.398942e-01</td>\n",
       "      <td>-7.148842e-01</td>\n",
       "      <td>-7.063295e-01</td>\n",
       "      <td>-5.754328e-01</td>\n",
       "      <td>-5.658819e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-3.860286e-01</td>\n",
       "      <td>-2.505501e-01</td>\n",
       "      <td>2.732257e-02</td>\n",
       "      <td>-1.988037e-01</td>\n",
       "      <td>3.037724e-02</td>\n",
       "      <td>-6.498947e-02</td>\n",
       "      <td>-3.547946e-01</td>\n",
       "      <td>-3.681058e-01</td>\n",
       "      <td>-2.669566e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.758614e-01</td>\n",
       "      <td>2.997444e-01</td>\n",
       "      <td>5.410998e-01</td>\n",
       "      <td>3.887412e-01</td>\n",
       "      <td>3.211351e-01</td>\n",
       "      <td>6.045375e-01</td>\n",
       "      <td>2.483278e-01</td>\n",
       "      <td>2.153658e-01</td>\n",
       "      <td>1.345729e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.208450e+00</td>\n",
       "      <td>2.970968e+00</td>\n",
       "      <td>2.510028e+00</td>\n",
       "      <td>3.049955e+00</td>\n",
       "      <td>3.516525e+00</td>\n",
       "      <td>2.185271e+00</td>\n",
       "      <td>2.933678e+00</td>\n",
       "      <td>3.080666e+00</td>\n",
       "      <td>3.944929e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       城镇居民家庭人均现金消费支出(元)  城镇居民家庭人均食品消费支出(元)  城镇居民家庭人均衣着消费支出(元)  \\\n",
       "count       3.100000e+01       3.100000e+01       3.100000e+01   \n",
       "mean       -4.476706e-16       5.372047e-17       7.735748e-16   \n",
       "std         1.016530e+00       1.016530e+00       1.016530e+00   \n",
       "min        -9.699876e-01      -1.499903e+00      -2.429229e+00   \n",
       "25%        -6.509137e-01      -8.070432e-01      -6.027281e-01   \n",
       "50%        -3.860286e-01      -2.505501e-01       2.732257e-02   \n",
       "75%         2.758614e-01       2.997444e-01       5.410998e-01   \n",
       "max         3.208450e+00       2.970968e+00       2.510028e+00   \n",
       "\n",
       "       城镇居民家庭人均居住消费支出(元)  城镇居民家庭人均家庭设备及用品消费支出(元)  城镇居民家庭人均医疗保健消费支出(元)  \\\n",
       "count       3.100000e+01            3.100000e+01         3.100000e+01   \n",
       "mean       -4.154383e-16           -5.192979e-16        -1.432546e-17   \n",
       "std         1.016530e+00            1.016530e+00         1.016530e+00   \n",
       "min        -1.728744e+00           -1.727060e+00        -2.064318e+00   \n",
       "25%        -4.666843e-01           -6.398942e-01        -7.148842e-01   \n",
       "50%        -1.988037e-01            3.037724e-02        -6.498947e-02   \n",
       "75%         3.887412e-01            3.211351e-01         6.045375e-01   \n",
       "max         3.049955e+00            3.516525e+00         2.185271e+00   \n",
       "\n",
       "       城镇居民家庭人均交通和通信消费支出(元)  城镇居民家庭人均文教娱乐服务消费支出(元)  城镇居民家庭人均其它消费支出(元)  \n",
       "count          3.100000e+01           3.100000e+01       3.100000e+01  \n",
       "mean           1.719055e-16           1.575800e-16      -1.298245e-16  \n",
       "std            1.016530e+00           1.016530e+00       1.016530e+00  \n",
       "min           -9.577224e-01          -1.657557e+00      -1.079172e+00  \n",
       "25%           -7.063295e-01          -5.754328e-01      -5.658819e-01  \n",
       "50%           -3.547946e-01          -3.681058e-01      -2.669566e-01  \n",
       "75%            2.483278e-01           2.153658e-01       1.345729e-01  \n",
       "max            2.933678e+00           3.080666e+00       3.944929e+00  "
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.iloc[:,1:10].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>城镇居民家庭人均现金消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均食品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均衣着消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均居住消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均家庭设备及用品消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均医疗保健消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均交通和通信消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均文教娱乐服务消费支出(元)</th>\n",
       "      <th>城镇居民家庭人均其它消费支出(元)</th>\n",
       "      <th>engle</th>\n",
       "      <th>cloth_per</th>\n",
       "      <th>house_per</th>\n",
       "      <th>device</th>\n",
       "      <th>medical</th>\n",
       "      <th>traffic</th>\n",
       "      <th>cultural</th>\n",
       "      <th>else</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>北京市</td>\n",
       "      <td>2.204052</td>\n",
       "      <td>1.661144</td>\n",
       "      <td>2.145452</td>\n",
       "      <td>1.095455</td>\n",
       "      <td>1.960906</td>\n",
       "      <td>2.185271</td>\n",
       "      <td>2.083249</td>\n",
       "      <td>2.322958</td>\n",
       "      <td>1.956402</td>\n",
       "      <td>0.320695</td>\n",
       "      <td>0.104738</td>\n",
       "      <td>0.079129</td>\n",
       "      <td>0.069116</td>\n",
       "      <td>0.066578</td>\n",
       "      <td>0.171607</td>\n",
       "      <td>0.145572</td>\n",
       "      <td>0.042564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>天津市</td>\n",
       "      <td>1.166808</td>\n",
       "      <td>1.232927</td>\n",
       "      <td>0.505966</td>\n",
       "      <td>1.222258</td>\n",
       "      <td>1.011110</td>\n",
       "      <td>1.952392</td>\n",
       "      <td>0.829528</td>\n",
       "      <td>0.676822</td>\n",
       "      <td>1.095712</td>\n",
       "      <td>0.358681</td>\n",
       "      <td>0.094652</td>\n",
       "      <td>0.097550</td>\n",
       "      <td>0.067619</td>\n",
       "      <td>0.077021</td>\n",
       "      <td>0.148196</td>\n",
       "      <td>0.114692</td>\n",
       "      <td>0.041584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>河北省</td>\n",
       "      <td>-0.753325</td>\n",
       "      <td>-1.232469</td>\n",
       "      <td>-0.570745</td>\n",
       "      <td>0.322352</td>\n",
       "      <td>-0.558872</td>\n",
       "      <td>0.364663</td>\n",
       "      <td>-0.540291</td>\n",
       "      <td>-0.798689</td>\n",
       "      <td>-0.481321</td>\n",
       "      <td>0.323232</td>\n",
       "      <td>0.118808</td>\n",
       "      <td>0.130302</td>\n",
       "      <td>0.067220</td>\n",
       "      <td>0.089530</td>\n",
       "      <td>0.135526</td>\n",
       "      <td>0.097012</td>\n",
       "      <td>0.038369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>山西省</td>\n",
       "      <td>-0.914969</td>\n",
       "      <td>-1.499903</td>\n",
       "      <td>-0.633766</td>\n",
       "      <td>-0.007935</td>\n",
       "      <td>-0.857180</td>\n",
       "      <td>-0.307346</td>\n",
       "      <td>-0.614879</td>\n",
       "      <td>-0.423119</td>\n",
       "      <td>-0.830337</td>\n",
       "      <td>0.311722</td>\n",
       "      <td>0.123143</td>\n",
       "      <td>0.127136</td>\n",
       "      <td>0.062557</td>\n",
       "      <td>0.079130</td>\n",
       "      <td>0.136929</td>\n",
       "      <td>0.125573</td>\n",
       "      <td>0.033811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>0.377288</td>\n",
       "      <td>-0.403194</td>\n",
       "      <td>2.510028</td>\n",
       "      <td>0.455130</td>\n",
       "      <td>0.381349</td>\n",
       "      <td>1.277224</td>\n",
       "      <td>-0.059946</td>\n",
       "      <td>0.252644</td>\n",
       "      <td>1.212589</td>\n",
       "      <td>0.300938</td>\n",
       "      <td>0.157461</td>\n",
       "      <td>0.098931</td>\n",
       "      <td>0.067805</td>\n",
       "      <td>0.080460</td>\n",
       "      <td>0.126384</td>\n",
       "      <td>0.117274</td>\n",
       "      <td>0.050762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>0.157520</td>\n",
       "      <td>0.019345</td>\n",
       "      <td>0.566466</td>\n",
       "      <td>0.223764</td>\n",
       "      <td>-0.219686</td>\n",
       "      <td>1.068716</td>\n",
       "      <td>-0.053979</td>\n",
       "      <td>0.014033</td>\n",
       "      <td>0.541488</td>\n",
       "      <td>0.350753</td>\n",
       "      <td>0.119488</td>\n",
       "      <td>0.099006</td>\n",
       "      <td>0.059164</td>\n",
       "      <td>0.081310</td>\n",
       "      <td>0.133532</td>\n",
       "      <td>0.112643</td>\n",
       "      <td>0.044111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>-0.334854</td>\n",
       "      <td>-0.822989</td>\n",
       "      <td>0.515734</td>\n",
       "      <td>0.322020</td>\n",
       "      <td>-0.497369</td>\n",
       "      <td>1.481670</td>\n",
       "      <td>-0.585044</td>\n",
       "      <td>-0.398651</td>\n",
       "      <td>0.112221</td>\n",
       "      <td>0.322622</td>\n",
       "      <td>0.134489</td>\n",
       "      <td>0.115113</td>\n",
       "      <td>0.060819</td>\n",
       "      <td>0.100291</td>\n",
       "      <td>0.116782</td>\n",
       "      <td>0.106567</td>\n",
       "      <td>0.043334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>-0.640888</td>\n",
       "      <td>-0.807090</td>\n",
       "      <td>0.634528</td>\n",
       "      <td>-0.395980</td>\n",
       "      <td>-0.834347</td>\n",
       "      <td>0.475687</td>\n",
       "      <td>-0.808936</td>\n",
       "      <td>-0.797868</td>\n",
       "      <td>-0.444696</td>\n",
       "      <td>0.354243</td>\n",
       "      <td>0.150544</td>\n",
       "      <td>0.105589</td>\n",
       "      <td>0.057919</td>\n",
       "      <td>0.088769</td>\n",
       "      <td>0.111504</td>\n",
       "      <td>0.093739</td>\n",
       "      <td>0.037692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>上海市</td>\n",
       "      <td>3.208450</td>\n",
       "      <td>2.970968</td>\n",
       "      <td>1.219676</td>\n",
       "      <td>3.049955</td>\n",
       "      <td>3.516525</td>\n",
       "      <td>0.733388</td>\n",
       "      <td>2.933678</td>\n",
       "      <td>3.080666</td>\n",
       "      <td>3.944929</td>\n",
       "      <td>0.335210</td>\n",
       "      <td>0.077331</td>\n",
       "      <td>0.093369</td>\n",
       "      <td>0.077593</td>\n",
       "      <td>0.043340</td>\n",
       "      <td>0.175708</td>\n",
       "      <td>0.144967</td>\n",
       "      <td>0.052486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>0.488895</td>\n",
       "      <td>0.573046</td>\n",
       "      <td>0.184244</td>\n",
       "      <td>-0.044117</td>\n",
       "      <td>0.666399</td>\n",
       "      <td>-0.168341</td>\n",
       "      <td>0.155904</td>\n",
       "      <td>1.060767</td>\n",
       "      <td>0.156925</td>\n",
       "      <td>0.365182</td>\n",
       "      <td>0.102072</td>\n",
       "      <td>0.085955</td>\n",
       "      <td>0.071482</td>\n",
       "      <td>0.056117</td>\n",
       "      <td>0.134780</td>\n",
       "      <td>0.148584</td>\n",
       "      <td>0.035828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>1.565504</td>\n",
       "      <td>1.401469</td>\n",
       "      <td>1.245515</td>\n",
       "      <td>0.566332</td>\n",
       "      <td>0.260921</td>\n",
       "      <td>0.860659</td>\n",
       "      <td>2.104393</td>\n",
       "      <td>1.804353</td>\n",
       "      <td>0.329278</td>\n",
       "      <td>0.342616</td>\n",
       "      <td>0.100923</td>\n",
       "      <td>0.079403</td>\n",
       "      <td>0.051304</td>\n",
       "      <td>0.057884</td>\n",
       "      <td>0.192472</td>\n",
       "      <td>0.144813</td>\n",
       "      <td>0.030597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>-0.386029</td>\n",
       "      <td>-0.253578</td>\n",
       "      <td>-0.571690</td>\n",
       "      <td>-0.059054</td>\n",
       "      <td>-0.613378</td>\n",
       "      <td>-0.477943</td>\n",
       "      <td>-0.594513</td>\n",
       "      <td>-0.012407</td>\n",
       "      <td>-0.267495</td>\n",
       "      <td>0.379549</td>\n",
       "      <td>0.106457</td>\n",
       "      <td>0.106805</td>\n",
       "      <td>0.058961</td>\n",
       "      <td>0.064026</td>\n",
       "      <td>0.117836</td>\n",
       "      <td>0.128537</td>\n",
       "      <td>0.037837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>福建省</td>\n",
       "      <td>0.609605</td>\n",
       "      <td>1.091260</td>\n",
       "      <td>-0.396177</td>\n",
       "      <td>1.191387</td>\n",
       "      <td>0.467159</td>\n",
       "      <td>-1.018168</td>\n",
       "      <td>0.495505</td>\n",
       "      <td>0.490433</td>\n",
       "      <td>0.075596</td>\n",
       "      <td>0.392590</td>\n",
       "      <td>0.086868</td>\n",
       "      <td>0.108902</td>\n",
       "      <td>0.065912</td>\n",
       "      <td>0.041858</td>\n",
       "      <td>0.148942</td>\n",
       "      <td>0.121085</td>\n",
       "      <td>0.033851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>江西省</td>\n",
       "      <td>-0.660940</td>\n",
       "      <td>-0.418430</td>\n",
       "      <td>-0.845201</td>\n",
       "      <td>-0.456726</td>\n",
       "      <td>0.034060</td>\n",
       "      <td>-1.438795</td>\n",
       "      <td>-0.706459</td>\n",
       "      <td>-0.504901</td>\n",
       "      <td>-0.751700</td>\n",
       "      <td>0.395095</td>\n",
       "      <td>0.107245</td>\n",
       "      <td>0.104514</td>\n",
       "      <td>0.080481</td>\n",
       "      <td>0.049366</td>\n",
       "      <td>0.119629</td>\n",
       "      <td>0.111115</td>\n",
       "      <td>0.032556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>山东省</td>\n",
       "      <td>0.107759</td>\n",
       "      <td>-0.408494</td>\n",
       "      <td>1.065591</td>\n",
       "      <td>0.535130</td>\n",
       "      <td>0.256502</td>\n",
       "      <td>0.193163</td>\n",
       "      <td>0.422214</td>\n",
       "      <td>-0.140498</td>\n",
       "      <td>-0.375216</td>\n",
       "      <td>0.320616</td>\n",
       "      <td>0.133037</td>\n",
       "      <td>0.107378</td>\n",
       "      <td>0.069750</td>\n",
       "      <td>0.067525</td>\n",
       "      <td>0.163163</td>\n",
       "      <td>0.106859</td>\n",
       "      <td>0.031681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>河南省</td>\n",
       "      <td>-0.593342</td>\n",
       "      <td>-1.004780</td>\n",
       "      <td>0.118388</td>\n",
       "      <td>-0.555314</td>\n",
       "      <td>0.078622</td>\n",
       "      <td>0.443643</td>\n",
       "      <td>-0.570904</td>\n",
       "      <td>-0.575022</td>\n",
       "      <td>-0.362290</td>\n",
       "      <td>0.329917</td>\n",
       "      <td>0.133284</td>\n",
       "      <td>0.099654</td>\n",
       "      <td>0.079965</td>\n",
       "      <td>0.086848</td>\n",
       "      <td>0.126844</td>\n",
       "      <td>0.104922</td>\n",
       "      <td>0.038566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>-0.404973</td>\n",
       "      <td>-0.197082</td>\n",
       "      <td>0.027323</td>\n",
       "      <td>-0.198804</td>\n",
       "      <td>0.080832</td>\n",
       "      <td>-0.602055</td>\n",
       "      <td>-0.790516</td>\n",
       "      <td>-0.368106</td>\n",
       "      <td>-0.605200</td>\n",
       "      <td>0.386805</td>\n",
       "      <td>0.123631</td>\n",
       "      <td>0.103703</td>\n",
       "      <td>0.075740</td>\n",
       "      <td>0.061968</td>\n",
       "      <td>0.105275</td>\n",
       "      <td>0.110314</td>\n",
       "      <td>0.032565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>-0.289860</td>\n",
       "      <td>-0.298529</td>\n",
       "      <td>-0.408151</td>\n",
       "      <td>-0.216065</td>\n",
       "      <td>0.215254</td>\n",
       "      <td>-0.298320</td>\n",
       "      <td>-0.354795</td>\n",
       "      <td>-0.112416</td>\n",
       "      <td>-0.445773</td>\n",
       "      <td>0.365496</td>\n",
       "      <td>0.108031</td>\n",
       "      <td>0.099981</td>\n",
       "      <td>0.076429</td>\n",
       "      <td>0.065698</td>\n",
       "      <td>0.130348</td>\n",
       "      <td>0.119988</td>\n",
       "      <td>0.034037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>广东省</td>\n",
       "      <td>1.759655</td>\n",
       "      <td>1.995863</td>\n",
       "      <td>-0.555620</td>\n",
       "      <td>2.249964</td>\n",
       "      <td>1.335565</td>\n",
       "      <td>0.390388</td>\n",
       "      <td>2.081693</td>\n",
       "      <td>1.459328</td>\n",
       "      <td>0.907739</td>\n",
       "      <td>0.364888</td>\n",
       "      <td>0.066562</td>\n",
       "      <td>0.104124</td>\n",
       "      <td>0.065334</td>\n",
       "      <td>0.050272</td>\n",
       "      <td>0.184954</td>\n",
       "      <td>0.128505</td>\n",
       "      <td>0.035361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>-0.392948</td>\n",
       "      <td>-0.250550</td>\n",
       "      <td>-1.514482</td>\n",
       "      <td>-0.267185</td>\n",
       "      <td>0.030377</td>\n",
       "      <td>-0.981612</td>\n",
       "      <td>0.205067</td>\n",
       "      <td>-0.400129</td>\n",
       "      <td>-0.845418</td>\n",
       "      <td>0.380571</td>\n",
       "      <td>0.080626</td>\n",
       "      <td>0.101557</td>\n",
       "      <td>0.074290</td>\n",
       "      <td>0.054438</td>\n",
       "      <td>0.171713</td>\n",
       "      <td>0.108241</td>\n",
       "      <td>0.028572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>海南省</td>\n",
       "      <td>-0.566217</td>\n",
       "      <td>0.244573</td>\n",
       "      <td>-2.429229</td>\n",
       "      <td>-0.476643</td>\n",
       "      <td>-0.843554</td>\n",
       "      <td>-1.187412</td>\n",
       "      <td>-0.012729</td>\n",
       "      <td>-0.792777</td>\n",
       "      <td>-1.079172</td>\n",
       "      <td>0.448077</td>\n",
       "      <td>0.058215</td>\n",
       "      <td>0.101019</td>\n",
       "      <td>0.056403</td>\n",
       "      <td>0.053072</td>\n",
       "      <td>0.165201</td>\n",
       "      <td>0.091940</td>\n",
       "      <td>0.026074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>0.174434</td>\n",
       "      <td>0.354916</td>\n",
       "      <td>0.915601</td>\n",
       "      <td>0.094969</td>\n",
       "      <td>0.836176</td>\n",
       "      <td>0.805599</td>\n",
       "      <td>-0.558581</td>\n",
       "      <td>-0.130316</td>\n",
       "      <td>-0.120995</td>\n",
       "      <td>0.375898</td>\n",
       "      <td>0.127304</td>\n",
       "      <td>0.095688</td>\n",
       "      <td>0.080420</td>\n",
       "      <td>0.076603</td>\n",
       "      <td>0.103810</td>\n",
       "      <td>0.105587</td>\n",
       "      <td>0.034706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>四川省</td>\n",
       "      <td>-0.203810</td>\n",
       "      <td>0.134419</td>\n",
       "      <td>-0.464870</td>\n",
       "      <td>-0.400627</td>\n",
       "      <td>0.113977</td>\n",
       "      <td>-0.821395</td>\n",
       "      <td>-0.182659</td>\n",
       "      <td>-0.431330</td>\n",
       "      <td>0.096063</td>\n",
       "      <td>0.394842</td>\n",
       "      <td>0.104047</td>\n",
       "      <td>0.093076</td>\n",
       "      <td>0.072391</td>\n",
       "      <td>0.054605</td>\n",
       "      <td>0.138297</td>\n",
       "      <td>0.101172</td>\n",
       "      <td>0.041561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>-0.833286</td>\n",
       "      <td>-0.590379</td>\n",
       "      <td>-0.959899</td>\n",
       "      <td>-1.183688</td>\n",
       "      <td>-0.633633</td>\n",
       "      <td>-1.336797</td>\n",
       "      <td>-0.706200</td>\n",
       "      <td>-0.382229</td>\n",
       "      <td>-0.964449</td>\n",
       "      <td>0.399044</td>\n",
       "      <td>0.109601</td>\n",
       "      <td>0.088564</td>\n",
       "      <td>0.066940</td>\n",
       "      <td>0.054363</td>\n",
       "      <td>0.126314</td>\n",
       "      <td>0.124733</td>\n",
       "      <td>0.030443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>云南省</td>\n",
       "      <td>-0.520885</td>\n",
       "      <td>-0.041694</td>\n",
       "      <td>-0.782180</td>\n",
       "      <td>-1.367255</td>\n",
       "      <td>-1.237246</td>\n",
       "      <td>-0.925649</td>\n",
       "      <td>0.291589</td>\n",
       "      <td>-0.776684</td>\n",
       "      <td>-1.078633</td>\n",
       "      <td>0.414797</td>\n",
       "      <td>0.104641</td>\n",
       "      <td>0.075446</td>\n",
       "      <td>0.045999</td>\n",
       "      <td>0.057603</td>\n",
       "      <td>0.184187</td>\n",
       "      <td>0.091601</td>\n",
       "      <td>0.025736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>西藏自治区</td>\n",
       "      <td>-0.947937</td>\n",
       "      <td>0.198770</td>\n",
       "      <td>-0.782810</td>\n",
       "      <td>-1.728744</td>\n",
       "      <td>-1.727060</td>\n",
       "      <td>-2.064318</td>\n",
       "      <td>-0.757568</td>\n",
       "      <td>-1.657557</td>\n",
       "      <td>-0.018660</td>\n",
       "      <td>0.500501</td>\n",
       "      <td>0.119622</td>\n",
       "      <td>0.075019</td>\n",
       "      <td>0.038862</td>\n",
       "      <td>0.039812</td>\n",
       "      <td>0.127087</td>\n",
       "      <td>0.049352</td>\n",
       "      <td>0.049744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>-0.290906</td>\n",
       "      <td>-0.242412</td>\n",
       "      <td>0.066711</td>\n",
       "      <td>-0.399963</td>\n",
       "      <td>-0.448020</td>\n",
       "      <td>0.417016</td>\n",
       "      <td>-0.804396</td>\n",
       "      <td>0.178088</td>\n",
       "      <td>-0.266957</td>\n",
       "      <td>0.370617</td>\n",
       "      <td>0.120810</td>\n",
       "      <td>0.095323</td>\n",
       "      <td>0.061217</td>\n",
       "      <td>0.079124</td>\n",
       "      <td>0.101067</td>\n",
       "      <td>0.134987</td>\n",
       "      <td>0.036855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>-0.883384</td>\n",
       "      <td>-0.885163</td>\n",
       "      <td>-0.476844</td>\n",
       "      <td>-1.118959</td>\n",
       "      <td>-0.912054</td>\n",
       "      <td>-0.064989</td>\n",
       "      <td>-0.957722</td>\n",
       "      <td>-0.575843</td>\n",
       "      <td>-0.526564</td>\n",
       "      <td>0.374133</td>\n",
       "      <td>0.126897</td>\n",
       "      <td>0.091992</td>\n",
       "      <td>0.060402</td>\n",
       "      <td>0.083736</td>\n",
       "      <td>0.108798</td>\n",
       "      <td>0.114872</td>\n",
       "      <td>0.039160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>青海省</td>\n",
       "      <td>-0.969988</td>\n",
       "      <td>-0.806996</td>\n",
       "      <td>-0.697732</td>\n",
       "      <td>-1.075142</td>\n",
       "      <td>-0.741540</td>\n",
       "      <td>-0.560534</td>\n",
       "      <td>-0.905835</td>\n",
       "      <td>-0.951249</td>\n",
       "      <td>-0.822796</td>\n",
       "      <td>0.393684</td>\n",
       "      <td>0.123323</td>\n",
       "      <td>0.096060</td>\n",
       "      <td>0.066987</td>\n",
       "      <td>0.074768</td>\n",
       "      <td>0.116146</td>\n",
       "      <td>0.094458</td>\n",
       "      <td>0.034586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>-0.440832</td>\n",
       "      <td>-0.822800</td>\n",
       "      <td>0.032994</td>\n",
       "      <td>-0.218057</td>\n",
       "      <td>-0.475641</td>\n",
       "      <td>0.212570</td>\n",
       "      <td>-0.311728</td>\n",
       "      <td>-0.330335</td>\n",
       "      <td>0.079905</td>\n",
       "      <td>0.332448</td>\n",
       "      <td>0.125062</td>\n",
       "      <td>0.104258</td>\n",
       "      <td>0.063188</td>\n",
       "      <td>0.078531</td>\n",
       "      <td>0.138922</td>\n",
       "      <td>0.113478</td>\n",
       "      <td>0.044122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>-0.790599</td>\n",
       "      <td>-0.892166</td>\n",
       "      <td>0.335179</td>\n",
       "      <td>-1.158460</td>\n",
       "      <td>-0.646155</td>\n",
       "      <td>-0.608374</td>\n",
       "      <td>-0.725139</td>\n",
       "      <td>-0.779968</td>\n",
       "      <td>-0.221175</td>\n",
       "      <td>0.362338</td>\n",
       "      <td>0.148415</td>\n",
       "      <td>0.088103</td>\n",
       "      <td>0.065695</td>\n",
       "      <td>0.069451</td>\n",
       "      <td>0.123162</td>\n",
       "      <td>0.099283</td>\n",
       "      <td>0.043561</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          地区  城镇居民家庭人均现金消费支出(元)  城镇居民家庭人均食品消费支出(元)  城镇居民家庭人均衣着消费支出(元)  \\\n",
       "0        北京市           2.204052           1.661144           2.145452   \n",
       "1        天津市           1.166808           1.232927           0.505966   \n",
       "2        河北省          -0.753325          -1.232469          -0.570745   \n",
       "3        山西省          -0.914969          -1.499903          -0.633766   \n",
       "4     内蒙古自治区           0.377288          -0.403194           2.510028   \n",
       "5        辽宁省           0.157520           0.019345           0.566466   \n",
       "6        吉林省          -0.334854          -0.822989           0.515734   \n",
       "7       黑龙江省          -0.640888          -0.807090           0.634528   \n",
       "8        上海市           3.208450           2.970968           1.219676   \n",
       "9        江苏省           0.488895           0.573046           0.184244   \n",
       "10       浙江省           1.565504           1.401469           1.245515   \n",
       "11       安徽省          -0.386029          -0.253578          -0.571690   \n",
       "12       福建省           0.609605           1.091260          -0.396177   \n",
       "13       江西省          -0.660940          -0.418430          -0.845201   \n",
       "14       山东省           0.107759          -0.408494           1.065591   \n",
       "15       河南省          -0.593342          -1.004780           0.118388   \n",
       "16       湖北省          -0.404973          -0.197082           0.027323   \n",
       "17       湖南省          -0.289860          -0.298529          -0.408151   \n",
       "18       广东省           1.759655           1.995863          -0.555620   \n",
       "19   广西壮族自治区          -0.392948          -0.250550          -1.514482   \n",
       "20       海南省          -0.566217           0.244573          -2.429229   \n",
       "21       重庆市           0.174434           0.354916           0.915601   \n",
       "22       四川省          -0.203810           0.134419          -0.464870   \n",
       "23       贵州省          -0.833286          -0.590379          -0.959899   \n",
       "24       云南省          -0.520885          -0.041694          -0.782180   \n",
       "25     西藏自治区          -0.947937           0.198770          -0.782810   \n",
       "26       陕西省          -0.290906          -0.242412           0.066711   \n",
       "27       甘肃省          -0.883384          -0.885163          -0.476844   \n",
       "28       青海省          -0.969988          -0.806996          -0.697732   \n",
       "29   宁夏回族自治区          -0.440832          -0.822800           0.032994   \n",
       "30  新疆维吾尔自治区          -0.790599          -0.892166           0.335179   \n",
       "\n",
       "    城镇居民家庭人均居住消费支出(元)  城镇居民家庭人均家庭设备及用品消费支出(元)  城镇居民家庭人均医疗保健消费支出(元)  \\\n",
       "0            1.095455                1.960906             2.185271   \n",
       "1            1.222258                1.011110             1.952392   \n",
       "2            0.322352               -0.558872             0.364663   \n",
       "3           -0.007935               -0.857180            -0.307346   \n",
       "4            0.455130                0.381349             1.277224   \n",
       "5            0.223764               -0.219686             1.068716   \n",
       "6            0.322020               -0.497369             1.481670   \n",
       "7           -0.395980               -0.834347             0.475687   \n",
       "8            3.049955                3.516525             0.733388   \n",
       "9           -0.044117                0.666399            -0.168341   \n",
       "10           0.566332                0.260921             0.860659   \n",
       "11          -0.059054               -0.613378            -0.477943   \n",
       "12           1.191387                0.467159            -1.018168   \n",
       "13          -0.456726                0.034060            -1.438795   \n",
       "14           0.535130                0.256502             0.193163   \n",
       "15          -0.555314                0.078622             0.443643   \n",
       "16          -0.198804                0.080832            -0.602055   \n",
       "17          -0.216065                0.215254            -0.298320   \n",
       "18           2.249964                1.335565             0.390388   \n",
       "19          -0.267185                0.030377            -0.981612   \n",
       "20          -0.476643               -0.843554            -1.187412   \n",
       "21           0.094969                0.836176             0.805599   \n",
       "22          -0.400627                0.113977            -0.821395   \n",
       "23          -1.183688               -0.633633            -1.336797   \n",
       "24          -1.367255               -1.237246            -0.925649   \n",
       "25          -1.728744               -1.727060            -2.064318   \n",
       "26          -0.399963               -0.448020             0.417016   \n",
       "27          -1.118959               -0.912054            -0.064989   \n",
       "28          -1.075142               -0.741540            -0.560534   \n",
       "29          -0.218057               -0.475641             0.212570   \n",
       "30          -1.158460               -0.646155            -0.608374   \n",
       "\n",
       "    城镇居民家庭人均交通和通信消费支出(元)  城镇居民家庭人均文教娱乐服务消费支出(元)  城镇居民家庭人均其它消费支出(元)     engle  \\\n",
       "0               2.083249               2.322958           1.956402  0.320695   \n",
       "1               0.829528               0.676822           1.095712  0.358681   \n",
       "2              -0.540291              -0.798689          -0.481321  0.323232   \n",
       "3              -0.614879              -0.423119          -0.830337  0.311722   \n",
       "4              -0.059946               0.252644           1.212589  0.300938   \n",
       "5              -0.053979               0.014033           0.541488  0.350753   \n",
       "6              -0.585044              -0.398651           0.112221  0.322622   \n",
       "7              -0.808936              -0.797868          -0.444696  0.354243   \n",
       "8               2.933678               3.080666           3.944929  0.335210   \n",
       "9               0.155904               1.060767           0.156925  0.365182   \n",
       "10              2.104393               1.804353           0.329278  0.342616   \n",
       "11             -0.594513              -0.012407          -0.267495  0.379549   \n",
       "12              0.495505               0.490433           0.075596  0.392590   \n",
       "13             -0.706459              -0.504901          -0.751700  0.395095   \n",
       "14              0.422214              -0.140498          -0.375216  0.320616   \n",
       "15             -0.570904              -0.575022          -0.362290  0.329917   \n",
       "16             -0.790516              -0.368106          -0.605200  0.386805   \n",
       "17             -0.354795              -0.112416          -0.445773  0.365496   \n",
       "18              2.081693               1.459328           0.907739  0.364888   \n",
       "19              0.205067              -0.400129          -0.845418  0.380571   \n",
       "20             -0.012729              -0.792777          -1.079172  0.448077   \n",
       "21             -0.558581              -0.130316          -0.120995  0.375898   \n",
       "22             -0.182659              -0.431330           0.096063  0.394842   \n",
       "23             -0.706200              -0.382229          -0.964449  0.399044   \n",
       "24              0.291589              -0.776684          -1.078633  0.414797   \n",
       "25             -0.757568              -1.657557          -0.018660  0.500501   \n",
       "26             -0.804396               0.178088          -0.266957  0.370617   \n",
       "27             -0.957722              -0.575843          -0.526564  0.374133   \n",
       "28             -0.905835              -0.951249          -0.822796  0.393684   \n",
       "29             -0.311728              -0.330335           0.079905  0.332448   \n",
       "30             -0.725139              -0.779968          -0.221175  0.362338   \n",
       "\n",
       "    cloth_per  house_per    device   medical   traffic  cultural      else  \n",
       "0    0.104738   0.079129  0.069116  0.066578  0.171607  0.145572  0.042564  \n",
       "1    0.094652   0.097550  0.067619  0.077021  0.148196  0.114692  0.041584  \n",
       "2    0.118808   0.130302  0.067220  0.089530  0.135526  0.097012  0.038369  \n",
       "3    0.123143   0.127136  0.062557  0.079130  0.136929  0.125573  0.033811  \n",
       "4    0.157461   0.098931  0.067805  0.080460  0.126384  0.117274  0.050762  \n",
       "5    0.119488   0.099006  0.059164  0.081310  0.133532  0.112643  0.044111  \n",
       "6    0.134489   0.115113  0.060819  0.100291  0.116782  0.106567  0.043334  \n",
       "7    0.150544   0.105589  0.057919  0.088769  0.111504  0.093739  0.037692  \n",
       "8    0.077331   0.093369  0.077593  0.043340  0.175708  0.144967  0.052486  \n",
       "9    0.102072   0.085955  0.071482  0.056117  0.134780  0.148584  0.035828  \n",
       "10   0.100923   0.079403  0.051304  0.057884  0.192472  0.144813  0.030597  \n",
       "11   0.106457   0.106805  0.058961  0.064026  0.117836  0.128537  0.037837  \n",
       "12   0.086868   0.108902  0.065912  0.041858  0.148942  0.121085  0.033851  \n",
       "13   0.107245   0.104514  0.080481  0.049366  0.119629  0.111115  0.032556  \n",
       "14   0.133037   0.107378  0.069750  0.067525  0.163163  0.106859  0.031681  \n",
       "15   0.133284   0.099654  0.079965  0.086848  0.126844  0.104922  0.038566  \n",
       "16   0.123631   0.103703  0.075740  0.061968  0.105275  0.110314  0.032565  \n",
       "17   0.108031   0.099981  0.076429  0.065698  0.130348  0.119988  0.034037  \n",
       "18   0.066562   0.104124  0.065334  0.050272  0.184954  0.128505  0.035361  \n",
       "19   0.080626   0.101557  0.074290  0.054438  0.171713  0.108241  0.028572  \n",
       "20   0.058215   0.101019  0.056403  0.053072  0.165201  0.091940  0.026074  \n",
       "21   0.127304   0.095688  0.080420  0.076603  0.103810  0.105587  0.034706  \n",
       "22   0.104047   0.093076  0.072391  0.054605  0.138297  0.101172  0.041561  \n",
       "23   0.109601   0.088564  0.066940  0.054363  0.126314  0.124733  0.030443  \n",
       "24   0.104641   0.075446  0.045999  0.057603  0.184187  0.091601  0.025736  \n",
       "25   0.119622   0.075019  0.038862  0.039812  0.127087  0.049352  0.049744  \n",
       "26   0.120810   0.095323  0.061217  0.079124  0.101067  0.134987  0.036855  \n",
       "27   0.126897   0.091992  0.060402  0.083736  0.108798  0.114872  0.039160  \n",
       "28   0.123323   0.096060  0.066987  0.074768  0.116146  0.094458  0.034586  \n",
       "29   0.125062   0.104258  0.063188  0.078531  0.138922  0.113478  0.044122  \n",
       "30   0.148415   0.088103  0.065695  0.069451  0.123162  0.099283  0.043561  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 建模"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = train.set_index('地区')  # 地区特征在这里没有用 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import AgglomerativeClustering\n",
    "from scipy.cluster.hierarchy import linkage, dendrogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "Z = linkage(train, method='average')\n",
    "p = dendrogram(Z,labels=train.index)\n",
    "plt.xticks(fontsize=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgglomerativeClustering(linkage='average', n_clusters=3)"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = AgglomerativeClustering(n_clusters=3, linkage='average')\n",
    "model.fit(train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "train['class'] = model.fit_predict(train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(list,\n",
       "            {0: ['北京市', '天津市', '浙江省', '广东省'],\n",
       "             1: ['河北省',\n",
       "              '山西省',\n",
       "              '内蒙古自治区',\n",
       "              '辽宁省',\n",
       "              '吉林省',\n",
       "              '黑龙江省',\n",
       "              '江苏省',\n",
       "              '安徽省',\n",
       "              '福建省',\n",
       "              '江西省',\n",
       "              '山东省',\n",
       "              '河南省',\n",
       "              '湖北省',\n",
       "              '湖南省',\n",
       "              '广西壮族自治区',\n",
       "              '海南省',\n",
       "              '重庆市',\n",
       "              '四川省',\n",
       "              '贵州省',\n",
       "              '云南省',\n",
       "              '西藏自治区',\n",
       "              '陕西省',\n",
       "              '甘肃省',\n",
       "              '青海省',\n",
       "              '宁夏回族自治区',\n",
       "              '新疆维吾尔自治区'],\n",
       "             2: ['上海市']})"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import collections\n",
    "class_dict = collections.defaultdict(list)\n",
    "for row in train.values:\n",
    "    class_dict[row[-1]].append(row[0])\n",
    "    \n",
    "class_dict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. 上海的消费水平在全国31省市自治区是独一档的\n",
    "2. 北京市, 天津市, 浙江省, 广东省在消费水平上是第二档的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
